Create a two-part educational infographic that visually explains how Java handles object memory during a while(rs.next()) loop reading from a ResultSet. Top Section: AI Timeline Context (from another domain): • Include a stylized, complex timeline tree diagram with AI project names (use placeholder boxes if needed). • Show branches with tags like “RAG,” “Memory Systems,” “Multi-Agent,” “Reasoning”—similar to a tech evolution chart. • Style: colorful, clean icons, Reddit logo in corner, title “From AIMemory community on Reddit.” Bottom Section: Java Memory Object Behavior: • Add a flowchart-like explanation of how Java creates and manages objects during a loop over a ResultSet. • Include: • A small database table called users with 3 rows (id + name: Alice, Bob, Charlie). • A while(rs.next()) diamond shape. • Heap Memory box where new User objects are created during each loop. • Two outcomes: • If reference is lost → arrow to trash bin labeled “Garbage Collector cleans it.” • If object is stored in List<User> → arrow to green box showing objects kept. • Add Hindi or Hinglish labels like: • “Har row ke liye naya object banega.” • “Object ka reference lost ho jayega, to Garbage Collector clean kar dega.” • “Agar List mei store kiya, to object permanent rehta hai.” • Use color coding: • Heap = light blue • Trash/GC = gray • Permanent List = green • Arrows and labels should be clean and readable. Style: • Educational + infographic layout • Modern UI style, no excessive shadows • Minimal but colorful • Legible fonts, labeled arrows • Clear section separation
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### **Image Generation Prompt for "Memory Me Objects Ka Behavior Kya Hoga?"** **Prompt:** Create a detailed and visually intuitive diagram to explain the behavior of objects in memory during a `while` loop that iterates over a database `ResultSet`. The diagram should include the following elements: 1. **Heap Memory Section:** - Show how new `User` objects are created in the heap memory during each iteration of the loop. - Highlight that each object corresponds to a row from the `ResultSet`. 2. **Garbage Collection:** - Illustrate how objects lose their reference after the loop ends and become eligible for garbage collection. - Use an arrow or icon to represent the Java Garbage Collector cleaning up unused objects. 3. **Permanent Storage (Optional):** - Show a scenario where objects are stored in a `List<User>` for permanent use. - Highlight the difference between temporary objects (eligible for garbage collection) and permanently stored objects. 4. **Flow of Execution:** - Include a flowchart-like representation of the `while` loop: - Start with `rs.next()` moving the cursor to the next row. - Show the creation of a new `User` object for each row. - End with either garbage collection or storage in a `List`. 5. **Annotations:** - Add labels and arrows to explain each step clearly. - Use Hindi/Hinglish annotations like: - "Har row ke liye naya object banega." - "Object ka reference lost ho jayega, to Garbage Collector clean kar dega." - "Agar List mei store kiya, to object permanent rehta hai." 6. **Color Coding:** - Use different colors for: - Heap memory (e.g., light blue). - Garbage-collected objects (e.g., grayed out). - Permanently stored objects (e.g., green). 7. **Database Table Example:** - Include a small table representation (e.g., `users` table with columns `id` and `name`) to show the source of data. --- ### **Expected Output:** The image should look like this: 1. **Top Section:** - A small database table (`users`) with rows and columns. 2. **Middle Section:** - A heap memory area showing multiple `User` objects being created during each iteration of the loop. - Arrows pointing from the `ResultSet` rows to the corresponding `User` objects in heap memory. 3. **Bottom Section:** - Two paths: - Path 1: Objects losing reference and being garbage collected (grayed out). - Path 2: Objects being stored in a `List<User>` for permanent use (highlighted in green). 4. **Annotations:** - Clear Hindi/Hinglish explanations for each step. --- This prompt will help generate a visually rich and easy-to-understand diagram for explaining the behavior of objects in memory! 😊
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
053
majicMIX realistic
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
037
majicMIX realistic
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 más 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
053
DreamShaper
https://images-wixmp-ed30a86b8c4ca887773594c2.wixmp.com/f/274ef350-8767-4522-923c-77019c9d2b27/dgh1upb-19d1af0e-e27a-4139-bf9d-9381c19a137f.png?token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJ1cm46YXBwOjdlMGQxODg5ODIyNjQzNzNhNWYwZDQxNWVhMGQyNmUwIiwiaXNzIjoidXJuOmFwcDo3ZTBkMTg4OTgyMjY0MzczYTVmMGQ0MTVlYTBkMjZlMCIsIm9iaiI6W1t7InBhdGgiOiJcL2ZcLzI3NGVmMzUwLTg3NjctNDUyMi05MjNjLTc3MDE5YzlkMmIyN1wvZGdoMXVwYi0xOWQxYWYwZS1lMjdhLTQxMzktYmY5ZC05MzgxYzE5YTEzN2YucG5nIn1dXSwiYXVkIjpbInVybjpzZXJ2aWNlOmZpbGUuZG93bmxvYWQiXX0.FI3h8ksfvhpTgraJvDjncHnbXJQB1yt5DVZ83XwFZ1c realistic version
013
Openjourney
### **Image Generation Prompt for "Memory Me Objects Ka Behavior Kya Hoga?"** **Prompt:** Create a detailed and visually intuitive diagram to explain the behavior of objects in memory during a `while` loop that iterates over a database `ResultSet`. The diagram should include the following elements: 1. **Heap Memory Section:** - Show how new `User` objects are created in the heap memory during each iteration of the loop. - Highlight that each object corresponds to a row from the `ResultSet`. 2. **Garbage Collection:** - Illustrate how objects lose their reference after the loop ends and become eligible for garbage collection. - Use an arrow or icon to represent the Java Garbage Collector cleaning up unused objects. 3. **Permanent Storage (Optional):** - Show a scenario where objects are stored in a `List<User>` for permanent use. - Highlight the difference between temporary objects (eligible for garbage collection) and permanently stored objects. 4. **Flow of Execution:** - Include a flowchart-like representation of the `while` loop: - Start with `rs.next()` moving the cursor to the next row. - Show the creation of a new `User` object for each row. - End with either garbage collection or storage in a `List`. 5. **Annotations:** - Add labels and arrows to explain each step clearly. - Use Hindi/Hinglish annotations like: - "Har row ke liye naya object banega." - "Object ka reference lost ho jayega, to Garbage Collector clean kar dega." - "Agar List mei store kiya, to object permanent rehta hai." 6. **Color Coding:** - Use different colors for: - Heap memory (e.g., light blue). - Garbage-collected objects (e.g., grayed out). - Permanently stored objects (e.g., green). 7. **Database Table Example:** - Include a small table representation (e.g., `users` table with columns `id` and `name`) to show the source of data. --- ### **Expected Output:** The image should look like this: 1. **Top Section:** - A small database table (`users`) with rows and columns. 2. **Middle Section:** - A heap memory area showing multiple `User` objects being created during each iteration of the loop. - Arrows pointing from the `ResultSet` rows to the corresponding `User` objects in heap memory. 3. **Bottom Section:** - Two paths: - Path 1: Objects losing reference and being garbage collected (grayed out). - Path 2: Objects being stored in a `List<User>` for permanent use (highlighted in green). 4. **Annotations:** - Clear Hindi/Hinglish explanations for each step. --- This prompt will help generate a visually rich and easy-to-understand diagram for explaining the behavior of objects in memory! 😊
1132
FLUX
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
037
majicMIX realistic
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 más 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1LH0m42gaTveALmExIhrS4OMTIlocZibCbLmGNw5puLDuCtOygqgI6S2pXIFi9DIjykEpbkgpYzPzCKSUopKiWEIoIFBRJkmnUKS96mZXgO2JAc1sMc/vODZ0iSBO5tYbqBVEFDas43R0swQQxco6rCEhhuFJ0FwCCeDJQB1PmQXIMdBTuIYAk4eiXuDRuTCvFipDYj3avfDWy49AJJ+G60OVcM6C11eZIBazSQL/nL2w39N7gCUvAZZRo6HVAA8E2lxcYuZDgGi02MG0RzW6yrEUqlMsJZTcPvA9xa37s6hqeBcTJ8wdrhLuzucVj5w9jU6Vd1557AczO4jvBtOlUZUE/9slwYBeNTR7zTLQCyDvc2IpsVhhTcO8Hyfda7uhrt7iS8XIGsgWkSJRZ5mrTUMljocWNcxgaAB7zoIJLjqJ23cDuLUFbF65AaBqNzyi0NA5R5klOoqIuMcxBrbLW3E8SbRc2KhYHE2YDZoa02Fz3v0mbxsTrYsaDTFxrBE+8dLS2J3HIxf+YMxaTawHL4ep/3Tr3GAAZsOtrXby67R/JvidJL6rmEvO72RqdIJLoLiH84B5nYp/DNDmvvpiCQTEgCBpk950nYbRMcxBpFpBPNosI3MxuCDsfHZP4OuAKkuLSQNraiHAw4ed/RRtkbpdYGqHd4yLSREtM2ediTYhxFy4m5guUXNW6mlpLgQS5hdJ7/AHS7vXkOJPPcg72CMLWnSYkSNQEkzYgDvSTE8/xO6p/ENkAEEnSATJE2Ow3iBtyhsbmeFcg2Yk3hHOO6AXblsiwI0TpIMWiSIvuAILiQ7xblorN7ZkF495ok8hJces2gc+ZFzmcvxTqFaQf6hzg87G3X5brZ0dL3NcQBTqCKke6yYAgGTz8rtAvqK2tKy2IVbxgxnT6hVPsn/K32Pac8ckFWOcYTsaz6bmiWnl9EfBQCFl2KUYqe0A6lWK+I2USMokIyRElBAoKJaOUqkIqibaU+LyhknGIwp3DEZNlLbWGkX5fuo1QJuVXE5XNZOIdR8lWeW42lSb3mOcTzBgeV/wBojxUHCsk7E+A5qVjWuiSA0eFz8VRueDCVBwDYOvyzHBnDiCAwSTMxLh4CeW5jaTMWEN4jE1ng2LWd1ukCB3Z0iOZuT5mU9k9WAQGkk85jzl+4H+W+/mnn4gBpe6CZhoaIaALkN8Cd3XJjzJZSsAdYhY5LEkZMq6WHc9wbuZNp26knYICABG4ug+tFhHUxMX5ft9BNOqE2m3RdwOknBMfc+/O3X3r3kpAfbnt8v4Teq3j8oSmmbk+HQx5wuzO2x1leJt5dBty5pDa8K74e4ZGKaXvqto027lxEnxaDA681YvyvLWgim6vXeAT3RDe6JcfQAlWCsYN3UfH5Sty1+qNJ0nl5/wDEroWR8DGvhy7VBuRO55R4bAei5d2rGVWuYXaZFjMjzXW+EeKDUrsptsHCNO8EACTG+xNt580VG4OOsQ1e5Sp5xOV5/SdSq6XiHMeWunrO5HM2v4rRcIl1V3ZsGpzyA1o/NBvbaATflJuNxA9pDmuxeILbgPaJ8QADsrj2Y4tmHrUaz9tYpzyHaNLR/qIHwRK3KOSviGc7qlJkH2j4E0sTpeRrA0uPIkAbC1o6mTcwAQFlHn6t+y6J7Z9P2k6XNLmkFwF41sBG4tMciudVHSov5IY9wDH7uoPkA/aNFEUZRFLmVWEggUFWWiAnGOTScpVS2YJANj4iQYPhIB9EOXVsGOVWphSCZCYcIUlZezrmWFCs6m3SWCRcEgAgETcRLpsbzaIUbEVnVD3j6ckO2LjcyeZN1IGHaBqeSfkPryRBUre9KteVXZk48Qm1gG9502gMbZv9xHLw3KjYjEF5BJ2AA5AAbADkEeJqg2a2Gj4nxKfy3KqlZwDWlccscCAJVRubiQQJTj6Dhu0idpELo3s/4YYartbQdIvYH9fr5qr9ormnFOY0BrWiPH6+uqn2XkxZdYHfao48zGspudsCUurgntiWkTstnw1krRTNeoCdMaQBztvy+fTyULiDGdpVYHACOg2E33P8LvZDzOGr3PtUcCIwvDONOGNdgD6LbloMkgbjSL8vNSsFk730KdV+IqtNUhtNlKnLNRMtDnNIgi9o6XVtwjnpoVX0y7uOdsdi1wsYPvHzM2iyTxAzG5ZrOEI+zVCXCGh3ZucJc0EiWjnF0K4WAD2f6Ew+ndSSLO/QzGvwpdUqUnx2rCWg8nFrjPmr/hztcHSq1R7zWkNO5BO5E2+ueyyb8SdQcJDhcmZJdJJdPjK1WBzXtMFWZzDfWTaSeZ/noSjVHz1gdUrHAUe6SJTVaBdh31CSXEgknmS6SZ57j4qybhSKWGZ+Gq9jiRuGgukjxgT6BT8ry7XhqlP8Rpu8pgkfNOYh5bl+DxLQC6jUba9w0iAfiQjhTg464hKgGYZ6AyDxXm/aPxWptP71zKlNzSH920DtBz0i4PMFZZy0PGzHNqsa9rWPLBUexohtMvsymB0ZTZTHxWdKEWYgBu0avbLY8cQkSNEVQwYiSgjKCrLRlGgjaFQCdJGFbqsl4mhBg285/ZDDlzIeCN7XEyIM6dwL77b9Cns1zOpiXmpVcXPMSTuYsJWjUtRpIb805mbOO0iYekSbKypZJVqm8/Xghgq5oua9oGr8MgEXtN7LqOSta6iwtZ2lV7Q4mSRH5nOPK1ut7QmxpK60w3JmbrdW1CgqOs5scgNOC74xb0nf0W44Ow7BRe4FrBBmo7YeU7/LxlWWe5G59Iue5oJEhjWyYHUmT6iFzp9XsyWSdM3vMwl2VVHEQW46xCCeROkcL4yjh6NapSJLnOdFR/RttcdJNh69QuaYiscRiCbnU4xPiYE/upuZ8TucwUmNDGNYGNA5DmSeZN//ACVNhqhBloJ8ks2MxrT0sgZm79JpcTmBp0uyDiADLhMy6foeizeZP+8B6/r9eim4bLq1V06TBM/XxSM+yypT0amxO11Q5l6TWj7cjJkFuLLHhwPgfrkf5W8yDiFr2BjxLT3SHGRsZ3sNp9dunP6mCqH8Dj5NJ+YCmZVSrCSKbyLA910b2BPIfwuHXpGbFUrwZq+JeGKLw6pTIBibesi/1dYjBVDSqFsneDe3rtPhdaqvUqNpjUQLyBvfkT0MeWw6LLVqffJnczI6+RVLCARiX0ys6nJyJ0vIWNYZkFriYg3gTy6GCPM+CUMn/wCir4ZrdTqVSo9gEQWOh9P/AEkfBZ7h3N3Na3WQdmhxPetpAaWTL+gPLoeWvyvH6XsqCSI7N3MFpnRcWN9TZ6uaAj134IMZ09YQ4M5xxxju3xtapyJaB/axo/UFUcLTe0DJDhsU8gfd1ZqUzFiHE6x5h025At6rO6UNjkkyrg7znzGyEkp0hIIVCJIEQQgjhBRJxGmibBDYoNcQZG6BPVVkRbkpuyQ0oiUZHxzJMndoTpmSBy8OQ8P91q8r43fTAYG2i8C5Ng0D+kb+gHK+MZUtCs8px9KiS59PWQ2GiYGo8z5fqtqu5HGWI+Of2ieopV15XPidVq5vS+z9pUNtOx90Hx/O79P6VyrNMV2tRzhsTZFisfVxBGo2HutFmtHQBP0MoeeSTtIJwo4mfp9MmlJZjyftE4DLWuu6T+i2FXD0qdJgaGi02/lZyrgKlNoJCS3F1Hw25OyGFx2lLg1xBDcCXNLHS4MAmSpWb5cXljt/0Hl1KaybKS0hztytHmeCdpYfkrCvzM221UsGyR8GHaNApkxtFiTb5fVlEzmvXptJc0MEe6PdHWZ3MwABe3iVt+HaQLB8+pTvEGTsqUyIGx+aCzAHE06NP7gs6zimIkmxJn8wi/QHkPh8lWVBe4W3zDg6rqOgSFn8yyp1KQ5p8PAyLnqIm3ilbl5nptAisvEaym7gGx3rRckD+ls38JmIC1OXgmR7xMl0NAdG9wdnAAQQA2eW85LAUyHDpznb1WjwlfQC19zzkTcnpEk/Ib+eXbcUPE1/wQYZxNBnWV/b8I6jANemS+n1LgLsHIB4sPFzSdlyosXQ8uz7s3A6rgzF5E/rzvuSALc6j2h5SGVW4qkPuq8kgbMq7vHk4d8ebuiLpNVltj9+kS1elK+9Mg4JBCdeEiFpRDbGiEE4QguxJ2yIWpT6cAE87geEkTPmCPRSKjQQbf7eiiuCHiVdNsSDdKN0qm4DeSIIgGPL5wfRNrhxBxSk4LDazdMgyrDL6ukwIuJJ6DwTtSAtz0grCQvE0eRYBsgBonz/AH3+AWgc6nRbNvSCP/I2J+KyGExpEwYH6+fMpWJxbqhuZT3u44mLZpXts948SxzXOQ+w2UfKa7Q8GOfj+wKi0AAZKm0tDiBEHqnaNKjruzzNun0VWrwrTob8uBptexu4mxufiiqtcad+XnHxUfJ89p0cI5tYXZt1M7JjKOIqVWQ0c7QQD8is91KuVPY/rPK67QWae0qVPE0fClSRH1Cusxb3SVS8N6W1XTIkTIEH+78Lv1VjxLjTTpOI71twCY8XU/fjyn0SVnNuBNbRv/5vlIGXPDnEFRuKMhZUYTAUbgys6rUlwt1bdvqN2nwutTmWlzSA4GLHYweh6FUvTDbY9oLmA3fGc8yLhLU4mLdVG4jyl1DqBfadvPf4LpuSYUNHiqzjvAB1Enn87rC1WkbduBnqNL6kSwVuk4tiK5m/L4D+PmtJw28Y/DVcG/3nCaZJ2qNux3qRpPgXLLYhveMdVL4exRoV2OMgEwTt6+hUGltu4dRyPpGbrVbKnoeP9SiqMIJBBBBgg7gjcHxTZC1ntIyzs8R2zR93iB2gjYVLCoP/AC7/APeso5bFTh0DDvMRkwcGIKCDkFeUkmphoJmyhVaSu85xPanWGhvg0AD5KncTsjKi45jOsRVbavSL+wzS7RpJIJ1CDDRYNcXbXJI9PFQCpJJTLmLrlVgNoxMzBBOY2E9SrR8ISCxKbSQ0V1PEhsd5Ko4hTKWIUShhSrPC4JO1pYYsWVWyIGV1YZYWudBhRvsJ+H6dU9hMCSYhHFtlXM9B6ezbgcZE02dZa52HLZkOaQ1w2PQErmVGvUovlpLHC1rEdV1rIsqrBuhoJY73mG7XenJ3iIKpuNfZ/Upg1dDoOzo58g8DbpNv2WfqNSuoxg4YfeMep6UWtkYye3n+Yrgf2gBrmtrEg7TqIafEd4AHzXSeImtxGHLmhxtIloJHnoe0x5yF52pixpmGuDpBIvqFtJcLgfKfitbwVx1VofcVna6ZMAkkx4SDcedkOuzew3dR38zydul9krFOh7ePlNtwSexqPMmla7mtcaX/AOjCAAPID/MtJmFKnVe19QGjUiGVqbu64cgKmzhf3KgIk2ndZbJcc2lXbVBlrrHRax6t/F8CtZi4DiwDTrBlha51CoD/AFRDHG/7gpq9MWZ8xTTXZQ/OWGCqvYdLtLmwIeLOJ5yyI9QfRVXF2LZ2Tw4agWkRMEWs4dYMEKIMSGANaNOn/CvDf/rqHSCPASFluMM9LqZDSYuLgg25QhppgTkw9msONq9ZhW5hSFQ76Z3mSfEfXqVtcowOXYmi7W+u2pFnCmS0eg3uuVO6hSsLmlan7lRw8ilNte7nP0mm1l+3CNz8Z1POqdHF5Xoa9xxFL7wBzSJdTBFRrDzlgcdJ73dbay5g5WPD/E2Kp1mdn94TUadBFnuJA0k8p29VBxenU7QIbqOkSDDZMDULG0XClVVeF6QtT2tn2mM/CMOQSXFBdLyywz5ABEj9kxVYCen10TuEpmxm230E9VoWnr/tyTdRzxNBq2evMrnMSTRUmrukAp0VI3WZrJgyOadvFSqVGYQDJVzkVTRUZqY17S6CCB7xBaDq3G87xIBR69GesU1GVXcI3Qws2i4Ok/3C3zCmUKZaZAkcxzHjHPoQnsfSbTrPaydO1yHGRvcQDcck9QIN+cSB+a4Hpz+CZ2BRmU0tQtwexk3B4MPgj06+QPPyK1eQ8MBxDi3+FByTAxTp1T7jntafDUdN/J0Lo+Dw4piOi896nqX/ACJ0m+r/AIdNq9YrB4RlFsNAnmVzf2p8avoHsaLnMfzIDHNI6EOBBHUELW8a8QtwlEvMO/o1NDyOrQ4w6Oi8/wCdY41qr6hJMm0ySByFyf1SmnqCruMz7bSoyT7xh4zHU8QdValoed30rT4upOMH0LVAxuALAHSHUz7r2zpPgZu13gb+l0klPYPGupElpsd2kBzHDo5jgQ4eYRGUGA9oWPvfrJGUcQvo910ub8x/K6dwtxjSxFHsajgQBEEDSBylog26z6hc/wAK/CYnuva3DVfzAONBx8d3Uj8W/wCVPjg7EsIqUQ5w3D6RLm+lSnI+aZrtO3a/I+4+sq3pgu9+ojPf+RNlnObNAgEkcg8NGkf0xceh9VjM5zHXMklWeFynHOH31DU3m947I35moYb8ZSK2TYEd6tiNJ5tZWZV+dKk6PgU0b0xgcRSr0i5G3Pj9RMYaL7uaHaTuR06GNh5qdlmUF5mC4D3onQ3n95U91jetyfIq8rZrhKFsPS1u/MdQnc96o6Hu3FmtpG0EkWVPjs0rVyTVqOfJmCe6Lz3W7NHgAFnOgLZE1UrAx3kzF5gKQcylUc/UNJfGhjWWllNgs2ebt4sLEl1M8pRKQ4qMAS5MbcUETkaiUl9gsMOsp/E0oF1MyKix5upGY4W0QqU34fbPSrV/8uJmCe9sD4cj5pgturCthUx2EclsIczEuqOYigLqwpOgOi8AmDzA3+Shsp3UkSSeUgjwvPyWtptQAu0xOxMrjEdfif8ABABMgh/4oLZA8oM+a0+XZZGILYns2Uy4cyx7ASR6ys5/8bUAOIA7jS0ecCAPg1bzEP0VcPjqI1tfRaHt5vpizh/mA0keLUDUWtnjvmdpE2Hia/KMrY2m6iYdTf3m9DIuB/7DzPRR854mZgmaK5MwQx4jvRydNg7zgHqEK2e0GUQ/tB2TgC10xE7GfwmeuxXIeN89qYisWuqNqMae65o0k+LgDpLo5gX+Sw/ZbiWfpD3PtBY/SQeKM9fiqrnaiGEzpBe1h/q7IvcGu8rKkeUt5TLiqMcmZZYucmJJQlEUSHLYigU9h6zmHUwlp6tJB+IUcJbV2YReI/WrOeZe4uPVxJPxKLUmwUqV2YURQKMJISgpzCrAU25OOTTlElohyCBQVcyk2+XYIt2laSlgWvp397yUvABpYLQYTjGEbLz340s3HBE9eAFG0TMY7InC8WScNkhqCCtdiCXC9wpeBwTS2QAvTU65TSGPWKuiDlhMfR4aDA7W0kx3Y69SqnFZaWSYsuuMoMLYdA8VjeKWsBOnZAq9SZ32gRL2aPniZBuYPDDT/DMxymFOyLiE0qfYuvT1F9M86bj7w/ym/kfO1VX3IG38KIHljoPI3H6rZW0tjMRKbDmWOfZk5uprD3HyXN/DqO5b0nos05yscwdqEqrcUHVNzM7VZLRLimyUolIKSMCBCKJAoKkvAEoJKMKJZY4CjSJRgrswojjUuU2CgXKYQGKc5NkoSiJXTiYkoIigqyJrMDn1SQC4x5rbZdmUMBdeVzN9ODb4qdl+bOaQ1xJaFj6jSK3Kieiq1B/K86e6qHtslZWXNJkGFT5Dj2PgalrxhxpGkykl1R0/uEcGGuYKMeZDx9Ulnd5rHZ1qgytsWQYhVOZ5aXpjS6xFs8AwaAFds55Xp7qtr7rUZtgtEhZ/F0l6iq0MMiI6iorIdR3dVe8qZXMKEVa5s4mHf+aIKSUZSSljBCBEjRKsmGEYSUaqZYRSEopQXQgi5QlIlCV0vmKlESiQldJhFGiQXSJcuSR+yCCSm33lzwzUIqC661kzu4PJEgsX1OHf+jHW++jxdmlEgspfzCC/uEwPEO6zWJQQXutH/TEJqusqsxsSqxyCCaeeb1P9QwklBBCMAISJBBUkiBGEEFEsIaCCC6XENBBBdLCEgggukwIIILp0/9k=
053
DreamShaper
https://images-wixmp-ed30a86b8c4ca887773594c2.wixmp.com/f/274ef350-8767-4522-923c-77019c9d2b27/dgh1upb-19d1af0e-e27a-4139-bf9d-9381c19a137f.png?token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJ1cm46YXBwOjdlMGQxODg5ODIyNjQzNzNhNWYwZDQxNWVhMGQyNmUwIiwiaXNzIjoidXJuOmFwcDo3ZTBkMTg4OTgyMjY0MzczYTVmMGQ0MTVlYTBkMjZlMCIsIm9iaiI6W1t7InBhdGgiOiJcL2ZcLzI3NGVmMzUwLTg3NjctNDUyMi05MjNjLTc3MDE5YzlkMmIyN1wvZGdoMXVwYi0xOWQxYWYwZS1lMjdhLTQxMzktYmY5ZC05MzgxYzE5YTEzN2YucG5nIn1dXSwiYXVkIjpbInVybjpzZXJ2aWNlOmZpbGUuZG93bmxvYWQiXX0.FI3h8ksfvhpTgraJvDjncHnbXJQB1yt5DVZ83XwFZ1c realistic version
013
Openjourney
Create a two-part educational infographic that visually explains how Java handles object memory during a while(rs.next()) loop reading from a ResultSet. Top Section: AI Timeline Context (from another domain): • Include a stylized, complex timeline tree diagram with AI project names (use placeholder boxes if needed). • Show branches with tags like “RAG,” “Memory Systems,” “Multi-Agent,” “Reasoning”—similar to a tech evolution chart. • Style: colorful, clean icons, Reddit logo in corner, title “From AIMemory community on Reddit.” Bottom Section: Java Memory Object Behavior: • Add a flowchart-like explanation of how Java creates and manages objects during a loop over a ResultSet. • Include: • A small database table called users with 3 rows (id + name: Alice, Bob, Charlie). • A while(rs.next()) diamond shape. • Heap Memory box where new User objects are created during each loop. • Two outcomes: • If reference is lost → arrow to trash bin labeled “Garbage Collector cleans it.” • If object is stored in List<User> → arrow to green box showing objects kept. • Add Hindi or Hinglish labels like: • “Har row ke liye naya object banega.” • “Object ka reference lost ho jayega, to Garbage Collector clean kar dega.” • “Agar List mei store kiya, to object permanent rehta hai.” • Use color coding: • Heap = light blue • Trash/GC = gray • Permanent List = green • Arrows and labels should be clean and readable. Style: • Educational + infographic layout • Modern UI style, no excessive shadows • Minimal but colorful • Legible fonts, labeled arrows • Clear section separation
032
FLUX
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
053
majicMIX realistic
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
037
majicMIX realistic
https://images-wixmp-ed30a86b8c4ca887773594c2.wixmp.com/f/274ef350-8767-4522-923c-77019c9d2b27/dgh1upb-19d1af0e-e27a-4139-bf9d-9381c19a137f.png?token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJ1cm46YXBwOjdlMGQxODg5ODIyNjQzNzNhNWYwZDQxNWVhMGQyNmUwIiwiaXNzIjoidXJuOmFwcDo3ZTBkMTg4OTgyMjY0MzczYTVmMGQ0MTVlYTBkMjZlMCIsIm9iaiI6W1t7InBhdGgiOiJcL2ZcLzI3NGVmMzUwLTg3NjctNDUyMi05MjNjLTc3MDE5YzlkMmIyN1wvZGdoMXVwYi0xOWQxYWYwZS1lMjdhLTQxMzktYmY5ZC05MzgxYzE5YTEzN2YucG5nIn1dXSwiYXVkIjpbInVybjpzZXJ2aWNlOmZpbGUuZG93bmxvYWQiXX0.FI3h8ksfvhpTgraJvDjncHnbXJQB1yt5DVZ83XwFZ1c realistic version
013
Openjourney
Create a two-part educational infographic that visually explains how Java handles object memory during a while(rs.next()) loop reading from a ResultSet. Top Section: AI Timeline Context (from another domain): • Include a stylized, complex timeline tree diagram with AI project names (use placeholder boxes if needed). • Show branches with tags like “RAG,” “Memory Systems,” “Multi-Agent,” “Reasoning”—similar to a tech evolution chart. • Style: colorful, clean icons, Reddit logo in corner, title “From AIMemory community on Reddit.” Bottom Section: Java Memory Object Behavior: • Add a flowchart-like explanation of how Java creates and manages objects during a loop over a ResultSet. • Include: • A small database table called users with 3 rows (id + name: Alice, Bob, Charlie). • A while(rs.next()) diamond shape. • Heap Memory box where new User objects are created during each loop. • Two outcomes: • If reference is lost → arrow to trash bin labeled “Garbage Collector cleans it.” • If object is stored in List<User> → arrow to green box showing objects kept. • Add Hindi or Hinglish labels like: • “Har row ke liye naya object banega.” • “Object ka reference lost ho jayega, to Garbage Collector clean kar dega.” • “Agar List mei store kiya, to object permanent rehta hai.” • Use color coding: • Heap = light blue • Trash/GC = gray • Permanent List = green • Arrows and labels should be clean and readable. Style: • Educational + infographic layout • Modern UI style, no excessive shadows • Minimal but colorful • Legible fonts, labeled arrows • Clear section separation
032
FLUX
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 más 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
053
DreamShaper
### **Image Generation Prompt for "Memory Me Objects Ka Behavior Kya Hoga?"** **Prompt:** Create a detailed and visually intuitive diagram to explain the behavior of objects in memory during a `while` loop that iterates over a database `ResultSet`. The diagram should include the following elements: 1. **Heap Memory Section:** - Show how new `User` objects are created in the heap memory during each iteration of the loop. - Highlight that each object corresponds to a row from the `ResultSet`. 2. **Garbage Collection:** - Illustrate how objects lose their reference after the loop ends and become eligible for garbage collection. - Use an arrow or icon to represent the Java Garbage Collector cleaning up unused objects. 3. **Permanent Storage (Optional):** - Show a scenario where objects are stored in a `List<User>` for permanent use. - Highlight the difference between temporary objects (eligible for garbage collection) and permanently stored objects. 4. **Flow of Execution:** - Include a flowchart-like representation of the `while` loop: - Start with `rs.next()` moving the cursor to the next row. - Show the creation of a new `User` object for each row. - End with either garbage collection or storage in a `List`. 5. **Annotations:** - Add labels and arrows to explain each step clearly. - Use Hindi/Hinglish annotations like: - "Har row ke liye naya object banega." - "Object ka reference lost ho jayega, to Garbage Collector clean kar dega." - "Agar List mei store kiya, to object permanent rehta hai." 6. **Color Coding:** - Use different colors for: - Heap memory (e.g., light blue). - Garbage-collected objects (e.g., grayed out). - Permanently stored objects (e.g., green). 7. **Database Table Example:** - Include a small table representation (e.g., `users` table with columns `id` and `name`) to show the source of data. --- ### **Expected Output:** The image should look like this: 1. **Top Section:** - A small database table (`users`) with rows and columns. 2. **Middle Section:** - A heap memory area showing multiple `User` objects being created during each iteration of the loop. - Arrows pointing from the `ResultSet` rows to the corresponding `User` objects in heap memory. 3. **Bottom Section:** - Two paths: - Path 1: Objects losing reference and being garbage collected (grayed out). - Path 2: Objects being stored in a `List<User>` for permanent use (highlighted in green). 4. **Annotations:** - Clear Hindi/Hinglish explanations for each step. --- This prompt will help generate a visually rich and easy-to-understand diagram for explaining the behavior of objects in memory! 😊
1132
FLUX
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
053
majicMIX realistic
Create a two-part educational infographic that visually explains how Java handles object memory during a while(rs.next()) loop reading from a ResultSet. Top Section: AI Timeline Context (from another domain): • Include a stylized, complex timeline tree diagram with AI project names (use placeholder boxes if needed). • Show branches with tags like “RAG,” “Memory Systems,” “Multi-Agent,” “Reasoning”—similar to a tech evolution chart. • Style: colorful, clean icons, Reddit logo in corner, title “From AIMemory community on Reddit.” Bottom Section: Java Memory Object Behavior: • Add a flowchart-like explanation of how Java creates and manages objects during a loop over a ResultSet. • Include: • A small database table called users with 3 rows (id + name: Alice, Bob, Charlie). • A while(rs.next()) diamond shape. • Heap Memory box where new User objects are created during each loop. • Two outcomes: • If reference is lost → arrow to trash bin labeled “Garbage Collector cleans it.” • If object is stored in List<User> → arrow to green box showing objects kept. • Add Hindi or Hinglish labels like: • “Har row ke liye naya object banega.” • “Object ka reference lost ho jayega, to Garbage Collector clean kar dega.” • “Agar List mei store kiya, to object permanent rehta hai.” • Use color coding: • Heap = light blue • Trash/GC = gray • Permanent List = green • Arrows and labels should be clean and readable. Style: • Educational + infographic layout • Modern UI style, no excessive shadows • Minimal but colorful • Legible fonts, labeled arrows • Clear section separation
032
FLUX
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
053
majicMIX realistic
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 más 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
053
DreamShaper
### **Image Generation Prompt for "Memory Me Objects Ka Behavior Kya Hoga?"** **Prompt:** Create a detailed and visually intuitive diagram to explain the behavior of objects in memory during a `while` loop that iterates over a database `ResultSet`. The diagram should include the following elements: 1. **Heap Memory Section:** - Show how new `User` objects are created in the heap memory during each iteration of the loop. - Highlight that each object corresponds to a row from the `ResultSet`. 2. **Garbage Collection:** - Illustrate how objects lose their reference after the loop ends and become eligible for garbage collection. - Use an arrow or icon to represent the Java Garbage Collector cleaning up unused objects. 3. **Permanent Storage (Optional):** - Show a scenario where objects are stored in a `List<User>` for permanent use. - Highlight the difference between temporary objects (eligible for garbage collection) and permanently stored objects. 4. **Flow of Execution:** - Include a flowchart-like representation of the `while` loop: - Start with `rs.next()` moving the cursor to the next row. - Show the creation of a new `User` object for each row. - End with either garbage collection or storage in a `List`. 5. **Annotations:** - Add labels and arrows to explain each step clearly. - Use Hindi/Hinglish annotations like: - "Har row ke liye naya object banega." - "Object ka reference lost ho jayega, to Garbage Collector clean kar dega." - "Agar List mei store kiya, to object permanent rehta hai." 6. **Color Coding:** - Use different colors for: - Heap memory (e.g., light blue). - Garbage-collected objects (e.g., grayed out). - Permanently stored objects (e.g., green). 7. **Database Table Example:** - Include a small table representation (e.g., `users` table with columns `id` and `name`) to show the source of data. --- ### **Expected Output:** The image should look like this: 1. **Top Section:** - A small database table (`users`) with rows and columns. 2. **Middle Section:** - A heap memory area showing multiple `User` objects being created during each iteration of the loop. - Arrows pointing from the `ResultSet` rows to the corresponding `User` objects in heap memory. 3. **Bottom Section:** - Two paths: - Path 1: Objects losing reference and being garbage collected (grayed out). - Path 2: Objects being stored in a `List<User>` for permanent use (highlighted in green). 4. **Annotations:** - Clear Hindi/Hinglish explanations for each step. --- This prompt will help generate a visually rich and easy-to-understand diagram for explaining the behavior of objects in memory! 😊
1132
FLUX
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
037
majicMIX realistic
https://images-wixmp-ed30a86b8c4ca887773594c2.wixmp.com/f/274ef350-8767-4522-923c-77019c9d2b27/dgh1upb-19d1af0e-e27a-4139-bf9d-9381c19a137f.png?token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJ1cm46YXBwOjdlMGQxODg5ODIyNjQzNzNhNWYwZDQxNWVhMGQyNmUwIiwiaXNzIjoidXJuOmFwcDo3ZTBkMTg4OTgyMjY0MzczYTVmMGQ0MTVlYTBkMjZlMCIsIm9iaiI6W1t7InBhdGgiOiJcL2ZcLzI3NGVmMzUwLTg3NjctNDUyMi05MjNjLTc3MDE5YzlkMmIyN1wvZGdoMXVwYi0xOWQxYWYwZS1lMjdhLTQxMzktYmY5ZC05MzgxYzE5YTEzN2YucG5nIn1dXSwiYXVkIjpbInVybjpzZXJ2aWNlOmZpbGUuZG93bmxvYWQiXX0.FI3h8ksfvhpTgraJvDjncHnbXJQB1yt5DVZ83XwFZ1c realistic version
013
Openjourney
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
053
majicMIX realistic
Create a two-part educational infographic that visually explains how Java handles object memory during a while(rs.next()) loop reading from a ResultSet. Top Section: AI Timeline Context (from another domain): • Include a stylized, complex timeline tree diagram with AI project names (use placeholder boxes if needed). • Show branches with tags like “RAG,” “Memory Systems,” “Multi-Agent,” “Reasoning”—similar to a tech evolution chart. • Style: colorful, clean icons, Reddit logo in corner, title “From AIMemory community on Reddit.” Bottom Section: Java Memory Object Behavior: • Add a flowchart-like explanation of how Java creates and manages objects during a loop over a ResultSet. • Include: • A small database table called users with 3 rows (id + name: Alice, Bob, Charlie). • A while(rs.next()) diamond shape. • Heap Memory box where new User objects are created during each loop. • Two outcomes: • If reference is lost → arrow to trash bin labeled “Garbage Collector cleans it.” • If object is stored in List<User> → arrow to green box showing objects kept. • Add Hindi or Hinglish labels like: • “Har row ke liye naya object banega.” • “Object ka reference lost ho jayega, to Garbage Collector clean kar dega.” • “Agar List mei store kiya, to object permanent rehta hai.” • Use color coding: • Heap = light blue • Trash/GC = gray • Permanent List = green • Arrows and labels should be clean and readable. Style: • Educational + infographic layout • Modern UI style, no excessive shadows • Minimal but colorful • Legible fonts, labeled arrows • Clear section separation
032
FLUX
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
037
majicMIX realistic
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 más 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
053
DreamShaper
### **Image Generation Prompt for "Memory Me Objects Ka Behavior Kya Hoga?"** **Prompt:** Create a detailed and visually intuitive diagram to explain the behavior of objects in memory during a `while` loop that iterates over a database `ResultSet`. The diagram should include the following elements: 1. **Heap Memory Section:** - Show how new `User` objects are created in the heap memory during each iteration of the loop. - Highlight that each object corresponds to a row from the `ResultSet`. 2. **Garbage Collection:** - Illustrate how objects lose their reference after the loop ends and become eligible for garbage collection. - Use an arrow or icon to represent the Java Garbage Collector cleaning up unused objects. 3. **Permanent Storage (Optional):** - Show a scenario where objects are stored in a `List<User>` for permanent use. - Highlight the difference between temporary objects (eligible for garbage collection) and permanently stored objects. 4. **Flow of Execution:** - Include a flowchart-like representation of the `while` loop: - Start with `rs.next()` moving the cursor to the next row. - Show the creation of a new `User` object for each row. - End with either garbage collection or storage in a `List`. 5. **Annotations:** - Add labels and arrows to explain each step clearly. - Use Hindi/Hinglish annotations like: - "Har row ke liye naya object banega." - "Object ka reference lost ho jayega, to Garbage Collector clean kar dega." - "Agar List mei store kiya, to object permanent rehta hai." 6. **Color Coding:** - Use different colors for: - Heap memory (e.g., light blue). - Garbage-collected objects (e.g., grayed out). - Permanently stored objects (e.g., green). 7. **Database Table Example:** - Include a small table representation (e.g., `users` table with columns `id` and `name`) to show the source of data. --- ### **Expected Output:** The image should look like this: 1. **Top Section:** - A small database table (`users`) with rows and columns. 2. **Middle Section:** - A heap memory area showing multiple `User` objects being created during each iteration of the loop. - Arrows pointing from the `ResultSet` rows to the corresponding `User` objects in heap memory. 3. **Bottom Section:** - Two paths: - Path 1: Objects losing reference and being garbage collected (grayed out). - Path 2: Objects being stored in a `List<User>` for permanent use (highlighted in green). 4. **Annotations:** - Clear Hindi/Hinglish explanations for each step. --- This prompt will help generate a visually rich and easy-to-understand diagram for explaining the behavior of objects in memory! 😊
1132
FLUX
https://images-wixmp-ed30a86b8c4ca887773594c2.wixmp.com/f/274ef350-8767-4522-923c-77019c9d2b27/dgh1upb-19d1af0e-e27a-4139-bf9d-9381c19a137f.png?token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJ1cm46YXBwOjdlMGQxODg5ODIyNjQzNzNhNWYwZDQxNWVhMGQyNmUwIiwiaXNzIjoidXJuOmFwcDo3ZTBkMTg4OTgyMjY0MzczYTVmMGQ0MTVlYTBkMjZlMCIsIm9iaiI6W1t7InBhdGgiOiJcL2ZcLzI3NGVmMzUwLTg3NjctNDUyMi05MjNjLTc3MDE5YzlkMmIyN1wvZGdoMXVwYi0xOWQxYWYwZS1lMjdhLTQxMzktYmY5ZC05MzgxYzE5YTEzN2YucG5nIn1dXSwiYXVkIjpbInVybjpzZXJ2aWNlOmZpbGUuZG93bmxvYWQiXX0.FI3h8ksfvhpTgraJvDjncHnbXJQB1yt5DVZ83XwFZ1c realistic version
013
Openjourney
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
037
majicMIX realistic
Create a two-part educational infographic that visually explains how Java handles object memory during a while(rs.next()) loop reading from a ResultSet. Top Section: AI Timeline Context (from another domain): • Include a stylized, complex timeline tree diagram with AI project names (use placeholder boxes if needed). • Show branches with tags like “RAG,” “Memory Systems,” “Multi-Agent,” “Reasoning”—similar to a tech evolution chart. • Style: colorful, clean icons, Reddit logo in corner, title “From AIMemory community on Reddit.” Bottom Section: Java Memory Object Behavior: • Add a flowchart-like explanation of how Java creates and manages objects during a loop over a ResultSet. • Include: • A small database table called users with 3 rows (id + name: Alice, Bob, Charlie). • A while(rs.next()) diamond shape. • Heap Memory box where new User objects are created during each loop. • Two outcomes: • If reference is lost → arrow to trash bin labeled “Garbage Collector cleans it.” • If object is stored in List<User> → arrow to green box showing objects kept. • Add Hindi or Hinglish labels like: • “Har row ke liye naya object banega.” • “Object ka reference lost ho jayega, to Garbage Collector clean kar dega.” • “Agar List mei store kiya, to object permanent rehta hai.” • Use color coding: • Heap = light blue • Trash/GC = gray • Permanent List = green • Arrows and labels should be clean and readable. Style: • Educational + infographic layout • Modern UI style, no excessive shadows • Minimal but colorful • Legible fonts, labeled arrows • Clear section separation
032
FLUX
### **Image Generation Prompt for "Memory Me Objects Ka Behavior Kya Hoga?"** **Prompt:** Create a detailed and visually intuitive diagram to explain the behavior of objects in memory during a `while` loop that iterates over a database `ResultSet`. The diagram should include the following elements: 1. **Heap Memory Section:** - Show how new `User` objects are created in the heap memory during each iteration of the loop. - Highlight that each object corresponds to a row from the `ResultSet`. 2. **Garbage Collection:** - Illustrate how objects lose their reference after the loop ends and become eligible for garbage collection. - Use an arrow or icon to represent the Java Garbage Collector cleaning up unused objects. 3. **Permanent Storage (Optional):** - Show a scenario where objects are stored in a `List<User>` for permanent use. - Highlight the difference between temporary objects (eligible for garbage collection) and permanently stored objects. 4. **Flow of Execution:** - Include a flowchart-like representation of the `while` loop: - Start with `rs.next()` moving the cursor to the next row. - Show the creation of a new `User` object for each row. - End with either garbage collection or storage in a `List`. 5. **Annotations:** - Add labels and arrows to explain each step clearly. - Use Hindi/Hinglish annotations like: - "Har row ke liye naya object banega." - "Object ka reference lost ho jayega, to Garbage Collector clean kar dega." - "Agar List mei store kiya, to object permanent rehta hai." 6. **Color Coding:** - Use different colors for: - Heap memory (e.g., light blue). - Garbage-collected objects (e.g., grayed out). - Permanently stored objects (e.g., green). 7. **Database Table Example:** - Include a small table representation (e.g., `users` table with columns `id` and `name`) to show the source of data. --- ### **Expected Output:** The image should look like this: 1. **Top Section:** - A small database table (`users`) with rows and columns. 2. **Middle Section:** - A heap memory area showing multiple `User` objects being created during each iteration of the loop. - Arrows pointing from the `ResultSet` rows to the corresponding `User` objects in heap memory. 3. **Bottom Section:** - Two paths: - Path 1: Objects losing reference and being garbage collected (grayed out). - Path 2: Objects being stored in a `List<User>` for permanent use (highlighted in green). 4. **Annotations:** - Clear Hindi/Hinglish explanations for each step. --- This prompt will help generate a visually rich and easy-to-understand diagram for explaining the behavior of objects in memory! 😊
1132
FLUX
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 más 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1LH0m42gaTveALmExIhrS4OMTIlocZibCbLmGNw5puLDuCtOygqgI6S2pXIFi9DIjykEpbkgpYzPzCKSUopKiWEIoIFBRJkmnUKS96mZXgO2JAc1sMc/vODZ0iSBO5tYbqBVEFDas43R0swQQxco6rCEhhuFJ0FwCCeDJQB1PmQXIMdBTuIYAk4eiXuDRuTCvFipDYj3avfDWy49AJJ+G60OVcM6C11eZIBazSQL/nL2w39N7gCUvAZZRo6HVAA8E2lxcYuZDgGi02MG0RzW6yrEUqlMsJZTcPvA9xa37s6hqeBcTJ8wdrhLuzucVj5w9jU6Vd1557AczO4jvBtOlUZUE/9slwYBeNTR7zTLQCyDvc2IpsVhhTcO8Hyfda7uhrt7iS8XIGsgWkSJRZ5mrTUMljocWNcxgaAB7zoIJLjqJ23cDuLUFbF65AaBqNzyi0NA5R5klOoqIuMcxBrbLW3E8SbRc2KhYHE2YDZoa02Fz3v0mbxsTrYsaDTFxrBE+8dLS2J3HIxf+YMxaTawHL4ep/3Tr3GAAZsOtrXby67R/JvidJL6rmEvO72RqdIJLoLiH84B5nYp/DNDmvvpiCQTEgCBpk950nYbRMcxBpFpBPNosI3MxuCDsfHZP4OuAKkuLSQNraiHAw4ed/RRtkbpdYGqHd4yLSREtM2ediTYhxFy4m5guUXNW6mlpLgQS5hdJ7/AHS7vXkOJPPcg72CMLWnSYkSNQEkzYgDvSTE8/xO6p/ENkAEEnSATJE2Ow3iBtyhsbmeFcg2Yk3hHOO6AXblsiwI0TpIMWiSIvuAILiQ7xblorN7ZkF495ok8hJces2gc+ZFzmcvxTqFaQf6hzg87G3X5brZ0dL3NcQBTqCKke6yYAgGTz8rtAvqK2tKy2IVbxgxnT6hVPsn/K32Pac8ckFWOcYTsaz6bmiWnl9EfBQCFl2KUYqe0A6lWK+I2USMokIyRElBAoKJaOUqkIqibaU+LyhknGIwp3DEZNlLbWGkX5fuo1QJuVXE5XNZOIdR8lWeW42lSb3mOcTzBgeV/wBojxUHCsk7E+A5qVjWuiSA0eFz8VRueDCVBwDYOvyzHBnDiCAwSTMxLh4CeW5jaTMWEN4jE1ng2LWd1ukCB3Z0iOZuT5mU9k9WAQGkk85jzl+4H+W+/mnn4gBpe6CZhoaIaALkN8Cd3XJjzJZSsAdYhY5LEkZMq6WHc9wbuZNp26knYICABG4ug+tFhHUxMX5ft9BNOqE2m3RdwOknBMfc+/O3X3r3kpAfbnt8v4Teq3j8oSmmbk+HQx5wuzO2x1leJt5dBty5pDa8K74e4ZGKaXvqto027lxEnxaDA681YvyvLWgim6vXeAT3RDe6JcfQAlWCsYN3UfH5Sty1+qNJ0nl5/wDEroWR8DGvhy7VBuRO55R4bAei5d2rGVWuYXaZFjMjzXW+EeKDUrsptsHCNO8EACTG+xNt580VG4OOsQ1e5Sp5xOV5/SdSq6XiHMeWunrO5HM2v4rRcIl1V3ZsGpzyA1o/NBvbaATflJuNxA9pDmuxeILbgPaJ8QADsrj2Y4tmHrUaz9tYpzyHaNLR/qIHwRK3KOSviGc7qlJkH2j4E0sTpeRrA0uPIkAbC1o6mTcwAQFlHn6t+y6J7Z9P2k6XNLmkFwF41sBG4tMciudVHSov5IY9wDH7uoPkA/aNFEUZRFLmVWEggUFWWiAnGOTScpVS2YJANj4iQYPhIB9EOXVsGOVWphSCZCYcIUlZezrmWFCs6m3SWCRcEgAgETcRLpsbzaIUbEVnVD3j6ckO2LjcyeZN1IGHaBqeSfkPryRBUre9KteVXZk48Qm1gG9502gMbZv9xHLw3KjYjEF5BJ2AA5AAbADkEeJqg2a2Gj4nxKfy3KqlZwDWlccscCAJVRubiQQJTj6Dhu0idpELo3s/4YYartbQdIvYH9fr5qr9ormnFOY0BrWiPH6+uqn2XkxZdYHfao48zGspudsCUurgntiWkTstnw1krRTNeoCdMaQBztvy+fTyULiDGdpVYHACOg2E33P8LvZDzOGr3PtUcCIwvDONOGNdgD6LbloMkgbjSL8vNSsFk730KdV+IqtNUhtNlKnLNRMtDnNIgi9o6XVtwjnpoVX0y7uOdsdi1wsYPvHzM2iyTxAzG5ZrOEI+zVCXCGh3ZucJc0EiWjnF0K4WAD2f6Ew+ndSSLO/QzGvwpdUqUnx2rCWg8nFrjPmr/hztcHSq1R7zWkNO5BO5E2+ueyyb8SdQcJDhcmZJdJJdPjK1WBzXtMFWZzDfWTaSeZ/noSjVHz1gdUrHAUe6SJTVaBdh31CSXEgknmS6SZ57j4qybhSKWGZ+Gq9jiRuGgukjxgT6BT8ry7XhqlP8Rpu8pgkfNOYh5bl+DxLQC6jUba9w0iAfiQjhTg464hKgGYZ6AyDxXm/aPxWptP71zKlNzSH920DtBz0i4PMFZZy0PGzHNqsa9rWPLBUexohtMvsymB0ZTZTHxWdKEWYgBu0avbLY8cQkSNEVQwYiSgjKCrLRlGgjaFQCdJGFbqsl4mhBg285/ZDDlzIeCN7XEyIM6dwL77b9Cns1zOpiXmpVcXPMSTuYsJWjUtRpIb805mbOO0iYekSbKypZJVqm8/Xghgq5oua9oGr8MgEXtN7LqOSta6iwtZ2lV7Q4mSRH5nOPK1ut7QmxpK60w3JmbrdW1CgqOs5scgNOC74xb0nf0W44Ow7BRe4FrBBmo7YeU7/LxlWWe5G59Iue5oJEhjWyYHUmT6iFzp9XsyWSdM3vMwl2VVHEQW46xCCeROkcL4yjh6NapSJLnOdFR/RttcdJNh69QuaYiscRiCbnU4xPiYE/upuZ8TucwUmNDGNYGNA5DmSeZN//ACVNhqhBloJ8ks2MxrT0sgZm79JpcTmBp0uyDiADLhMy6foeizeZP+8B6/r9eim4bLq1V06TBM/XxSM+yypT0amxO11Q5l6TWj7cjJkFuLLHhwPgfrkf5W8yDiFr2BjxLT3SHGRsZ3sNp9dunP6mCqH8Dj5NJ+YCmZVSrCSKbyLA910b2BPIfwuHXpGbFUrwZq+JeGKLw6pTIBibesi/1dYjBVDSqFsneDe3rtPhdaqvUqNpjUQLyBvfkT0MeWw6LLVqffJnczI6+RVLCARiX0ys6nJyJ0vIWNYZkFriYg3gTy6GCPM+CUMn/wCir4ZrdTqVSo9gEQWOh9P/AEkfBZ7h3N3Na3WQdmhxPetpAaWTL+gPLoeWvyvH6XsqCSI7N3MFpnRcWN9TZ6uaAj134IMZ09YQ4M5xxxju3xtapyJaB/axo/UFUcLTe0DJDhsU8gfd1ZqUzFiHE6x5h025At6rO6UNjkkyrg7znzGyEkp0hIIVCJIEQQgjhBRJxGmibBDYoNcQZG6BPVVkRbkpuyQ0oiUZHxzJMndoTpmSBy8OQ8P91q8r43fTAYG2i8C5Ng0D+kb+gHK+MZUtCs8px9KiS59PWQ2GiYGo8z5fqtqu5HGWI+Of2ieopV15XPidVq5vS+z9pUNtOx90Hx/O79P6VyrNMV2tRzhsTZFisfVxBGo2HutFmtHQBP0MoeeSTtIJwo4mfp9MmlJZjyftE4DLWuu6T+i2FXD0qdJgaGi02/lZyrgKlNoJCS3F1Hw25OyGFx2lLg1xBDcCXNLHS4MAmSpWb5cXljt/0Hl1KaybKS0hztytHmeCdpYfkrCvzM221UsGyR8GHaNApkxtFiTb5fVlEzmvXptJc0MEe6PdHWZ3MwABe3iVt+HaQLB8+pTvEGTsqUyIGx+aCzAHE06NP7gs6zimIkmxJn8wi/QHkPh8lWVBe4W3zDg6rqOgSFn8yyp1KQ5p8PAyLnqIm3ilbl5nptAisvEaym7gGx3rRckD+ls38JmIC1OXgmR7xMl0NAdG9wdnAAQQA2eW85LAUyHDpznb1WjwlfQC19zzkTcnpEk/Ib+eXbcUPE1/wQYZxNBnWV/b8I6jANemS+n1LgLsHIB4sPFzSdlyosXQ8uz7s3A6rgzF5E/rzvuSALc6j2h5SGVW4qkPuq8kgbMq7vHk4d8ebuiLpNVltj9+kS1elK+9Mg4JBCdeEiFpRDbGiEE4QguxJ2yIWpT6cAE87geEkTPmCPRSKjQQbf7eiiuCHiVdNsSDdKN0qm4DeSIIgGPL5wfRNrhxBxSk4LDazdMgyrDL6ukwIuJJ6DwTtSAtz0grCQvE0eRYBsgBonz/AH3+AWgc6nRbNvSCP/I2J+KyGExpEwYH6+fMpWJxbqhuZT3u44mLZpXts948SxzXOQ+w2UfKa7Q8GOfj+wKi0AAZKm0tDiBEHqnaNKjruzzNun0VWrwrTob8uBptexu4mxufiiqtcad+XnHxUfJ89p0cI5tYXZt1M7JjKOIqVWQ0c7QQD8is91KuVPY/rPK67QWae0qVPE0fClSRH1Cusxb3SVS8N6W1XTIkTIEH+78Lv1VjxLjTTpOI71twCY8XU/fjyn0SVnNuBNbRv/5vlIGXPDnEFRuKMhZUYTAUbgys6rUlwt1bdvqN2nwutTmWlzSA4GLHYweh6FUvTDbY9oLmA3fGc8yLhLU4mLdVG4jyl1DqBfadvPf4LpuSYUNHiqzjvAB1Enn87rC1WkbduBnqNL6kSwVuk4tiK5m/L4D+PmtJw28Y/DVcG/3nCaZJ2qNux3qRpPgXLLYhveMdVL4exRoV2OMgEwTt6+hUGltu4dRyPpGbrVbKnoeP9SiqMIJBBBBgg7gjcHxTZC1ntIyzs8R2zR93iB2gjYVLCoP/AC7/APeso5bFTh0DDvMRkwcGIKCDkFeUkmphoJmyhVaSu85xPanWGhvg0AD5KncTsjKi45jOsRVbavSL+wzS7RpJIJ1CDDRYNcXbXJI9PFQCpJJTLmLrlVgNoxMzBBOY2E9SrR8ISCxKbSQ0V1PEhsd5Ko4hTKWIUShhSrPC4JO1pYYsWVWyIGV1YZYWudBhRvsJ+H6dU9hMCSYhHFtlXM9B6ezbgcZE02dZa52HLZkOaQ1w2PQErmVGvUovlpLHC1rEdV1rIsqrBuhoJY73mG7XenJ3iIKpuNfZ/Upg1dDoOzo58g8DbpNv2WfqNSuoxg4YfeMep6UWtkYye3n+Yrgf2gBrmtrEg7TqIafEd4AHzXSeImtxGHLmhxtIloJHnoe0x5yF52pixpmGuDpBIvqFtJcLgfKfitbwVx1VofcVna6ZMAkkx4SDcedkOuzew3dR38zydul9krFOh7ePlNtwSexqPMmla7mtcaX/AOjCAAPID/MtJmFKnVe19QGjUiGVqbu64cgKmzhf3KgIk2ndZbJcc2lXbVBlrrHRax6t/F8CtZi4DiwDTrBlha51CoD/AFRDHG/7gpq9MWZ8xTTXZQ/OWGCqvYdLtLmwIeLOJ5yyI9QfRVXF2LZ2Tw4agWkRMEWs4dYMEKIMSGANaNOn/CvDf/rqHSCPASFluMM9LqZDSYuLgg25QhppgTkw9msONq9ZhW5hSFQ76Z3mSfEfXqVtcowOXYmi7W+u2pFnCmS0eg3uuVO6hSsLmlan7lRw8ilNte7nP0mm1l+3CNz8Z1POqdHF5Xoa9xxFL7wBzSJdTBFRrDzlgcdJ73dbay5g5WPD/E2Kp1mdn94TUadBFnuJA0k8p29VBxenU7QIbqOkSDDZMDULG0XClVVeF6QtT2tn2mM/CMOQSXFBdLyywz5ABEj9kxVYCen10TuEpmxm230E9VoWnr/tyTdRzxNBq2evMrnMSTRUmrukAp0VI3WZrJgyOadvFSqVGYQDJVzkVTRUZqY17S6CCB7xBaDq3G87xIBR69GesU1GVXcI3Qws2i4Ok/3C3zCmUKZaZAkcxzHjHPoQnsfSbTrPaydO1yHGRvcQDcck9QIN+cSB+a4Hpz+CZ2BRmU0tQtwexk3B4MPgj06+QPPyK1eQ8MBxDi3+FByTAxTp1T7jntafDUdN/J0Lo+Dw4piOi896nqX/ACJ0m+r/AIdNq9YrB4RlFsNAnmVzf2p8avoHsaLnMfzIDHNI6EOBBHUELW8a8QtwlEvMO/o1NDyOrQ4w6Oi8/wCdY41qr6hJMm0ySByFyf1SmnqCruMz7bSoyT7xh4zHU8QdValoed30rT4upOMH0LVAxuALAHSHUz7r2zpPgZu13gb+l0klPYPGupElpsd2kBzHDo5jgQ4eYRGUGA9oWPvfrJGUcQvo910ub8x/K6dwtxjSxFHsajgQBEEDSBylog26z6hc/wAK/CYnuva3DVfzAONBx8d3Uj8W/wCVPjg7EsIqUQ5w3D6RLm+lSnI+aZrtO3a/I+4+sq3pgu9+ojPf+RNlnObNAgEkcg8NGkf0xceh9VjM5zHXMklWeFynHOH31DU3m947I35moYb8ZSK2TYEd6tiNJ5tZWZV+dKk6PgU0b0xgcRSr0i5G3Pj9RMYaL7uaHaTuR06GNh5qdlmUF5mC4D3onQ3n95U91jetyfIq8rZrhKFsPS1u/MdQnc96o6Hu3FmtpG0EkWVPjs0rVyTVqOfJmCe6Lz3W7NHgAFnOgLZE1UrAx3kzF5gKQcylUc/UNJfGhjWWllNgs2ebt4sLEl1M8pRKQ4qMAS5MbcUETkaiUl9gsMOsp/E0oF1MyKix5upGY4W0QqU34fbPSrV/8uJmCe9sD4cj5pgturCthUx2EclsIczEuqOYigLqwpOgOi8AmDzA3+Shsp3UkSSeUgjwvPyWtptQAu0xOxMrjEdfif8ABABMgh/4oLZA8oM+a0+XZZGILYns2Uy4cyx7ASR6ys5/8bUAOIA7jS0ecCAPg1bzEP0VcPjqI1tfRaHt5vpizh/mA0keLUDUWtnjvmdpE2Hia/KMrY2m6iYdTf3m9DIuB/7DzPRR854mZgmaK5MwQx4jvRydNg7zgHqEK2e0GUQ/tB2TgC10xE7GfwmeuxXIeN89qYisWuqNqMae65o0k+LgDpLo5gX+Sw/ZbiWfpD3PtBY/SQeKM9fiqrnaiGEzpBe1h/q7IvcGu8rKkeUt5TLiqMcmZZYucmJJQlEUSHLYigU9h6zmHUwlp6tJB+IUcJbV2YReI/WrOeZe4uPVxJPxKLUmwUqV2YURQKMJISgpzCrAU25OOTTlElohyCBQVcyk2+XYIt2laSlgWvp397yUvABpYLQYTjGEbLz340s3HBE9eAFG0TMY7InC8WScNkhqCCtdiCXC9wpeBwTS2QAvTU65TSGPWKuiDlhMfR4aDA7W0kx3Y69SqnFZaWSYsuuMoMLYdA8VjeKWsBOnZAq9SZ32gRL2aPniZBuYPDDT/DMxymFOyLiE0qfYuvT1F9M86bj7w/ym/kfO1VX3IG38KIHljoPI3H6rZW0tjMRKbDmWOfZk5uprD3HyXN/DqO5b0nos05yscwdqEqrcUHVNzM7VZLRLimyUolIKSMCBCKJAoKkvAEoJKMKJZY4CjSJRgrswojjUuU2CgXKYQGKc5NkoSiJXTiYkoIigqyJrMDn1SQC4x5rbZdmUMBdeVzN9ODb4qdl+bOaQ1xJaFj6jSK3Kieiq1B/K86e6qHtslZWXNJkGFT5Dj2PgalrxhxpGkykl1R0/uEcGGuYKMeZDx9Ulnd5rHZ1qgytsWQYhVOZ5aXpjS6xFs8AwaAFds55Xp7qtr7rUZtgtEhZ/F0l6iq0MMiI6iorIdR3dVe8qZXMKEVa5s4mHf+aIKSUZSSljBCBEjRKsmGEYSUaqZYRSEopQXQgi5QlIlCV0vmKlESiQldJhFGiQXSJcuSR+yCCSm33lzwzUIqC661kzu4PJEgsX1OHf+jHW++jxdmlEgspfzCC/uEwPEO6zWJQQXutH/TEJqusqsxsSqxyCCaeeb1P9QwklBBCMAISJBBUkiBGEEFEsIaCCC6XENBBBdLCEgggukwIIILp0/9k=
053
DreamShaper
https://images-wixmp-ed30a86b8c4ca887773594c2.wixmp.com/f/274ef350-8767-4522-923c-77019c9d2b27/dgh1upb-19d1af0e-e27a-4139-bf9d-9381c19a137f.png?token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJ1cm46YXBwOjdlMGQxODg5ODIyNjQzNzNhNWYwZDQxNWVhMGQyNmUwIiwiaXNzIjoidXJuOmFwcDo3ZTBkMTg4OTgyMjY0MzczYTVmMGQ0MTVlYTBkMjZlMCIsIm9iaiI6W1t7InBhdGgiOiJcL2ZcLzI3NGVmMzUwLTg3NjctNDUyMi05MjNjLTc3MDE5YzlkMmIyN1wvZGdoMXVwYi0xOWQxYWYwZS1lMjdhLTQxMzktYmY5ZC05MzgxYzE5YTEzN2YucG5nIn1dXSwiYXVkIjpbInVybjpzZXJ2aWNlOmZpbGUuZG93bmxvYWQiXX0.FI3h8ksfvhpTgraJvDjncHnbXJQB1yt5DVZ83XwFZ1c realistic version
013
Openjourney
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s0H0Z2ItMBp7Tef7mNuAjPfRTo66oYj2V7z8mNDi2traPITxs7zUeSMFt3QqemcthyMBLVoCYuamPpS7DE6xy29pFPFRE/MT3RCxXNHy/abAy5iPLHYrxqfZ8Y2fpxMsaIyLJltMOF6mC7xQ4nujJdLzwourr7hFc46XRpYaMZRdSasl9yHbbT9RMAMyPAboYl1airl48YZCxaOjdhSWpnTRgMl1u2YUbhgTyilIspqVed+HvRBPo/olJEsTp3tH+WooWJ1EA5nYDhrMP2q39UjJAesqk9Zjj6u9m21319lR0+3O7lyaucFAyWuzZ+9Yh2+0ACgPVXAb9p5nuoNUH8xJWRqxoxgteArVPLsScT3AagBqGqkRiatTZ4nLujm/dW8czj8BHshaKK5nE84pYebM1Hz/QM0s/X4AfHzi8ehTTF2dMs7HCaL6ffQdYc0/RGfaTartx8MIk6BtrSJsuavtI6sN9DUjmKjnB27J5rEVM1WXK7PoO1ymFEw9WWWh1rQg+r4GlBuJGoXhfpP0R62yswHWli+N60647g34YOy5yzJaOpqr+rZTtDMhU94gpapdVGFcKHnAJC6m4STPmiwC6/CPp6zPeVTqIB7QDGB9L9BfwlqKgfRt1pZ+ySer+E1HIHXG19EbR6yxyH2y1B4qLp7wYOLuHi0nGMkFY4k5c2/UY7jlFpXea9wghI6hQoUScKERChGIOM29JMkeolg4+raZKO0YVQ1+4AecU7oHZb8m3f6cvvE4fCNH6eWMvJmEDUH4GXjXml4fhWKp6J5Ara1OR9WOVZoiqWpr0pf468H6mYWsUc8a+cOW1r7JTWB3mJHSSzernMvukr+Ulf7YgWU0JOwd+Q+d0Sti1ys3Hg2grZMSzaq0HBY70tMpKXeCP6mhWNaKo3V7cYi6YetwbAe28Y5GlUl8uh4v8nejxdl1O89mHlEW1TeqTrY9ijIQ9a2oqptAruEDrRMvHuHAZRyQliKuWCguC+73GzEnR8urVOS4mIwgnY0pdXW3WbgMhzg2J0I5pe/IYtxqw4VPPV2UiToWVemKNp+e6Iloxdjvg90UshaYKDYO0/5i6mg0s1XXmbl0JkBbOpwq2PkPnfB8iKf0emerCALVaa4uCmIm9c3MzcTFqo2wRpPpBKlg9YMdgy7YpPSDpe71VTQbBlFLtGk3fWab8+yIkyfWLM0Ibam7h/htOn2nqyRbraXYkn5zPzuiqWybeYn53QVtUzqMePjSAoFTFMpuTuzsY9IwRP0LZbzjYDmcttTuAxgzaZ16gGCqKKNgzqd5NSd53CItjFxaDZT4xxaJmS6zh8TFLY9h6apU7v2x0NrgdbJ15wtcAcfOJVrm3FJ15CAZbGOiijG18torzCjPedRqGJ+HlBCQl68fdHgQPFu6B+iEwLHXh5mCmjBVJh2yye10MRbWxZh23HM93qVa0Yux3nxjh2pSO5o6xG817YYc1MWo85Vdm/Fl49G+mp/8TIkmdMMr1ij1Zdim4BTgBWhpH0EFqvKPmfoI922Wf8A1ZdebgR9MyshwEDxKaiaSM/9KVhMxZIRbziY1AM6BCz/AKQeUGPRbOLWIKfqOw5Gj/3GDn8KHnByPZUhfxUvNzoByO2B3QuxeqScgyE5gOACgd0dFWYUqilTy8iwQo5dwKV1mg4x1BlAoUKFHHHgO6OZxwMdw08vA01msCzkQLQgNQRUHMbRsil9CbF6i1WqUdiEVzIVmAPMOp5xoC2fbAbS9iEu0yp6igYGW/4sUJ/EFHZAZeI1TrJJx5/gx70nWO5appphevcnUN+omKnZxWg2nHl8mNP9LtlAdXOTyyDxlmvb1x2RnOiZVWrs8/kxyehqU453BrivQmWiZcUns46ogyxeVCcgzVPAK3xjjSc+81BkPHXHkpvoXA1Op5EMPELHJaFmJrqdSy2RHtE0sxO35pDUemOkSpoBUmDM+TcmKUBWpyHfugjoypLOfnX5RBny7pu6xnx2QRsApKY8e4RwxhotTs+BFs61IjX/AEW6BBlM7DMELxIpXsr2xlWi0q4j6E6CSLtlTfjDK7NO4rWm4RbW7CNhsShApA28ImoKCkewopbuZ0pNu7PmSdaVXM/GINp0gTguA26/2gcWjwGAsblTGznotAl6ysk8fOsM2Bav4fO7HujyxtUMm0VHEYw5YerVjwA3mBbCi/mSjJ7Ja+QUnNdWtIjWNSSXbM5RO0E5cMDia7NRiXpLRzIl5V6tMxq1dkJ/yFGeWRsZVJRnfTl4gS1i8WGpVPb8+ECqRcF0OVli8MTi3OKpNSjEbDFtGspt2M7GUu7N8bhmSt2zE6yR3q//ALCJWhDUXfelsBxukjvUQxbRSyje9OxZfxhrQk+6yH3cexqnuMX7MZjLLNQ8ANblozcT3xGlrrMEtPWe7OYatXLDy74gwSMOvC1SV+DZO0JP9XMWZrVgw/CQQO6PqLR80PLVhkQCOBFR3GPlOyvje2R9NdEQUs8uWa1RFGOfsgjuIHIxHEXq2cVYMgQxYJdFJ952btOHcBEikIQYsNz5YdSpyIIPOKr0f0i0sTltM5l9VNCVYg4NgvtAnGleEW6BOlNDyphd2RbxUCpW9Qr7LU5kE501iIZMWtmTbPPvC8rI42qR8SO+HlmA8dhz7Ir6SgpApccDAqaVG1SPaET5NtphMy1OMKfe2ccttIFS5lkqbSutQpChtXpQEg1yO2HIIqFDNslB0ZTkRzGsEbwceUPRG0jaFlSnmOaKiksdwEQzluZT6ZreLsqRgXFZjkahQqBzNT+ERn7N6qUPecVG4bfLtidpy2tabTMmzDRa3m3KMFQb6ADtO2ANttBdiTyGoAZAcoBI26cvlU78dl+SOxiTYjUOu1D/AEEP4KYixJsBo6tQkKatQV6uTV3UPfBi6etyPSC9kkBBU507BugZOl3WKnMEjsNIKW6ZSWd+EDIbwqis0pcECnapJ2mCtj/kng0B4L2T+SeDecEDhXeUn4Md0IPpF4x9EdFR/u0r7vnHzroWZSYp3iPojog9bMm6o76+cMy+n5iOKXYT8QxChQooM8+R5tndTRlIOwjbjHq2dz9U9nxg11dhHYfIR5Mmooqa9oFd2RipTZ6P+BCOspA2Wzy6ZY6sDBixz/WAUz1j51QMTrmtwcWJPZSkFbCtKAYDcAPCKK6VrvcZwKkpad3xDOhbP1wQAu05V4xfLHZVKUcAqwpTVwipaInKoxqeyvhBG3aQcS+rVaZ1y5R57FKc5pIaxMJTajHQf06AQ5AGHLLbGX6TVUJUG831m8hsg3pXSkxVpWhatGJOrOgpnlnFWm1rU478++Nf4fh5QjdsSxMlTjk3Ye0njZVP/UbvWVAbR8yjjfh2/IgtNa9YuExe9af2QBU0NY02U1p5akZLwCPSB63W3UPID94CVJMHNKdeTeG0Hy84EKlImL0FcfButps0mT9CWb1k6XL951XmzBfOPpOQbjKRkaKf7e8kfijB/RpZvWW+QtMFYudwRWYf1BY3gpUEbfkGAk9RSolZILKY9iJo2feXHMYHiM/jwIiXBp3FGrOwo8ZY9hRJBBtFmDYECmdCMK7RTFTvEQrXYiBRXYAjIqX71x7oNkRzcEC1cKM2tipWS2T5SPKWTNnG+1xipRFWvVuk4ka92UWPRk6YyL62XcemNCCOOBwrsiWFA1R7EpESknwFGcel7TlFFkVqVAeYdQH1VPPH8u2Lr0h0rLsslprkCg6oP1mpgo+cqx87dJNLNOmu7MTeYsd52kdwGQGA38xjDU7vPLZeoPttpr1VwUH8x947/CIcImJOjrG8x1RFLOxoqjEk7IjYabcmKxWVpjKiKWZiAqgVJJyAi56f0Oti0fc6rTZ0xRMbPBKuZcs+6rKLza2w1YWnof0VSzy77N9Iwo81cwD/AMqRhUVyMwYn6udQA9LqCWJKAULX3IrWgFxEWp2CvaaYQN7sHMm7Io85bxRveoD95aKe66fxQ5phsFG+PNEi9VdY668hRhzFD+EQ3pVq3ecTxHVph5S5kIQbs6UULu+fGBuj5V5q6hj8IIl+sBuPiIlsLCQtFyfHQh2J6ERvPoy0mJkkKTjQEdlD4d0YTKlgzGUmhOKnvp2RdfR/pZpMwA4UPaDnyzi+E1K8GLyw8qkJL3dG5xCtdrutSH7PODoGGRFYqWkbWfWNxiqU4w3M2hQdRtPgYfeOwdv7Rw8sE1Y1pqyAgYbY+3uHwht5rHMkxWoM1546DWzfUKvbFXLE7oZk6Re9gQKnZgIG1hyViaRzhG2pT/MqSas7dC22K1uCCWy3Z/tBB7deGNIr0uaAuBrQYkbs4iWzSBIurgNe0whLD55aI23iqdOGaW4R07aleXeHv4cgwPlANJhB+ceMePOJULsJPbT4Q1WHqVNQjlMXEYj5k83QP6Ne9ImpTYw3YlR+s9kBDE7QM+7MFfZYFTwIIJ4gVhjSEopMZTqJgyyo89JS5afol2Zr0lhsr8YGOaQY0DIMwFBmxCji2A74O2/0Y2+WK+qWZ/pOGPY109giYopxdS0Ic7ehJ9CNmvWqZMP1JRHN3WncrRsixQ/RFod5Mue0xGR2mKhDAqQJa3sjl/Mi+iK5biYwsz1cyups9xyB8uY2QaRqisBbYl5Tr+cRDmhrX9RjiNe0ajx1HkdcRCVnYCpC6ugvChQovKBQo9jyIOETDc2YACSQABUk4AAZmOjQRkfpR6bX71mkN9GMJjj6590H3B/Vwzi4cIObsgH6TulX8TNuoT6pKhPtbXI36hqA3mKI7VMdT5pJrHtmaXX6QtQDJKXmOypwXiQeBjkh1yjFWWyJWiNGTJ7hJa1OFTkqgmlWbUK4bzgKkgRrfRboqtlW8WUdX6RmXrMNmJAlS/s4k/W92KP0d6cy7NJKpY19YCSrXzd2AtUFiwGFa1OWAwATTnSe02s/SzSV1S16sscEGZ3mp3wLTYCqJ6Gn6f6c2WQD6tv4iYBQUPUH4x1afcBrGTaa0tMtM55sxrzE8AAMlUalGyIMxyYaQ4mJjGxDaTVgtotiovjMsAvzs+Ec6ZHWWmVMO3LllHVlGQ1KKfiOZju7ViTkDgN9MTA31NVQcqSivfM6scu6tNeuI8yf9IN2Hz2w5bLRdFBme6BdYmKvqDiKyhlhHgE7Y111b5wiy6GoaUisuL8uoxPmM4JdHLVcIR6rsJqBwNYXxCeXNHdDWHqJVGntLVdTZ+iukCJLIThQ3SdW0Q1OTE4CK7oW2FMzRR89kGpmkEJreEYGLxVaq0uRTLDOnVbitz57hR7SFHqjFsKPQY8hRxwR0XMzHOI9qWjERIsEsjrHWD5Q1pI9bl8YBd4fmn/HWbgyNWPRHEOSkJPEwQmrt2Q+DdKHdXvPlEvSi1o3LzEQrU3WwyGHZBBBeljbTvH+IF8x+j2lKHvQO+jmy+stEpf+oDyl/SHuUjnG6SphGRjNfRHoy6rTmGq4nE0Zzy6gr96NAtDlUYjOmHE4DvpDMFaOpm4ypmmoLgreZ3Z3vAsc2YniK0X+gLDtYZQAAAZAADgMBHVYSk9SVGyOyYGWuqMCMNYPiDtETmeKx0k6UWWWpUzbzjUlGodhaoUcK1gHrsWQi2y02TTS0AeqnZQnsYChHYdwiT/teXt7AT4CMdm9Olr1ZeG9iPBT4w/ZOml4iqCmujmtNwoPGDjKYTwiexrLaZlj3vyuPFYhWnpGFr9GaDWSgXiTeqOyKfN6XWP1dT66U9MqCapNNVWvUrvEUDpB0im2phLQFUJACA1LHVeOvHVl4wTz3AVCOzTT8Sx9OfSG85WkyiElmoZlJJcbKlQQvjwzze0TyTiYtkzok0qzvabW9wKOrKQgu7HBFLYqoJIrSuFcopLmnGDjqdJqCtE6d4bGMeKI6OAgyi7lqzxjqEOCOEEJm1RBK01PawpJxhNlEqxWYnE4DxjnoiynCU5pIn2VaKBr189XGO7XPCL9pshsG3t84aecoB2DvOweZgZPmliScz80itK71NOriVThkjv6CdyTU5w9YJdWrqEMSULGggvZ5QUUEE3ZC+GourPM9kM2TquU1H5HdBw2afIly5vty5lbpxwKkhkJ+qwwO8EEa6V6c30hI1eUbJ6LxLtNlmWeaoZGAeh1H2WI2EdXGDVOMk8yLHWlTi3F7P7XKJL0+pF0315BuWHwjz+ImHFWNDljBXpr0PezdaWCUYmj0xps+zh2wG0Pa1ly7j5gmnA4+NYTq4JLuodw+Nc92gBMsanLDhDLWD7Xd+8WKZoxJYxQJvmTKn8qfvEK0T1TIqN4UL2H2oYd0DPC07XmkvMErYPtdgh6XZlXE47zHto0hXWW4kxDaYzmndEasVboQdoK7J0p71TqyHLM/OyBtpe8xMSLVNCi4vOI8mUWNBEx01Kq83O0Fq+PU5kyyxoInkBFrsFBvJzPzsh2TKCDxMQLVOvHcMo692S6aoQu+8xmsGNFeyOJgakoDF8N2s/CDLSTLIUqVNEJU5qWRWoRqzyOO2Je1zsHpU13sbJ0FdTY5N0AAJQj7SkhjzYE84LWlqlF2tU8Ex/Vc7YqPo2tVLMVo5KzWoAppQhG9o0UYk5mLLZnZpjswACgIorXYzknmooK+xnF86kVDcz50mq0uV2Tr0RNK6RlyZZmTGuqOZJ1ADWTsh5mjKulukZtttAlSQWFSssDKg9qaTqrt1AdqC1Y5Tp5tXshjpb0ymziUQlJfug5j7bD2ju9kZY0qROjOjlstNGSSxU5O/UXkW9ofdrGjdFuhkmQA8wCbN95hVVOxFP6jjwyi1hYLOlogpT4LYyyX6N5wUtMny1OxVeZUnACpu4k0HOCMj0X+9axTXSVTvMzvi+u1ZirqHXP6UHbePFIhaY0xIlkS5k6Wt6t4FhW6KXhTOpqFpsZiMocoxvG8hKrOea0QRK9GElpSsJ8wTGFRfulaH2QVFGBpTWcScIpWntATbKzK0sEA0vJR0NcgWyWuxqHdGgWzphYvrTL/CXMbjjdpDY6e2UKUuu6EUKFBdIOYoxjpQjzL8PUxEHfK2uhln8PXqvWlcEUkKpxFbpzOOeGuI0/QRNfVktTNadYcVz7K8YtXSmfYHq9lWbKb/42VDLP3SHJTvG4QBkW4gjXTINjThrHIxRezNaNOjWj2o2fjowDOsrLmp8YjXYvn+0ZMwUmyzX3hie3BvGIdp0PJfGXNTg3VPb+0FfkUVPhl9YP+yntHcizsdXPKLBN0S6YhOagMO1YgzJDnAtTdSkC5FH8GUXeV30IwlImLGp2R2HLgk9VBmdZ+yNp3Q4mjtbNh3nh8YcmyA1K+yMlGAH774i6LFRq2tGNl69WDp8y9kKAZDYPM7THUizM24bYIJIUZAeMOxzlyCp4HW82cSJIUUH+YU+ZTAYsch5x6STlhvPkI6SWFx17dZiEOZezlhovewwtnpRdZxY7AP3jQPQ9Nb1twa6g8CKHyijubqkn2m+aco0f0L2EmY0ymCjHia0ENUtm2Z+IUYJ9DU7ZZVmIUdQykUIMZnpvoA/rWMtbyHEHDv3xqgj2IjNoyIVZQ2PlvSjnrGprtrAZ4UKF4G38R+oNxL0d9bhChQb2EaP1ERnzgtIyHCFCgZbDeC78hjSeQhiyZV10hQo6OwNb6/vkEehSBrfIDAEGatQRUHEajBDpD/xU/wD138TChRfU7gvgPrM0D0Y/8O/+sf8Axyos+jvZ/E//AJHhQoRluW1u/LqxaQ/lzP8ATf8ASYonoyQesnmgqEUA0xAqcAdUKFER2YVP6cuqNBWOzChRCKTO/SJanW0FFdgpVaqGIU4TMwMDFOOC4YZwoUNLuofwezBtomGpxPaYYM1vePaYUKIewNTvM7kzWr7R7TEzVChQLLqOzPbP7Ih0QoUAx2l3UIwvrDiPGFCiUFLc9tHtHj5mGYUKOBluexwmZhQo4rlwHY9GYhQoJB8CNbfaHAeMbL6GP+GfiY9hQzHumHjt5Ggy46hQoFmSz//Z
053
majicMIX realistic