Take the generated image and provide some slight bronze highlighting Prompts

Take the generated image and provide some slight bronze highlighting.

Using the generated image, change the outer rim to a colour between bronze and gold, and change Level 2 to Level 3, leave everything else the same.

Using the input image, change the dark coloured areas to bronze, and update all occurrences from 101 to 102.

Using the uploaded photo, change the green, and blue areas to bronze, leaving the white / gray. Change all occurrences of 101 to 102.

Using the uploaded photo, change the green colour to bronze, leaving the white / gray background, and make sure all occurrences of 101 are replaced with 102.

a person in a metal suit with a chain, in the style of gum bichromate, camilla d'errico, light bronze and pink, disfigured forms, webcam photography, religious subjects, donna huanca --s 1000 --c 100 --w 1000 --v 5.2 --style raw --ar 70:87

recreate image and make it brighter

Using the input image, change the outer rim to a tarnished / aged rose gold colour, change 102 for a star in a tarnished / aged rose gold colour, change Level 2 for Certified, and change flower / leaf print for stars in the same rose gold colour.

Using the input image, change the outer rim to a tarnished gold colour, change any occurrence of 102 to 103, and Level 2 to Level 3

Using the input image, change the bronze colour to silver, 102 to 103, and Level 1 to Level 2.

# Keeps 589 bright, boosts jewelry shine, replaces background, and maps to Casinofi duotone. import cv2, numpy as np from google.colab import files from PIL import Image # Upload your image when prompted up = files.upload() fn = list(up.keys())[0] img_bgr = cv2.imdecode(np.frombuffer(up[fn], np.uint8), cv2.IMREAD_COLOR) # --- Palette (BGR) --- HEX = lambda h: (int(h[5:7],16), int(h[3:5],16), int(h[1:3],16)) SHADOW = np.array(HEX("#0F1011"), np.float32) MID = np.array(HEX("#8E7A55"), np.float32) HILITE = np.array(HEX("#E6D2A1"), np.float32) HILITE_PLUS = np.array(HEX("#EBDDB7"), np.float32) # extra-bright cream for 589 # --- Helper: gradient map (shadow -> mid -> highlight) --- def gradient_map(gray01): g = gray01[...,None] t1 = np.clip(g/0.5, 0, 1) t2 = np.clip((g-0.5)/0.5, 0, 1) low = SHADOW*(1-t1) + MID*t1 high = MID*(1-t2) + HILITE*t2 return np.where(g<=0.5, low, high) hsv = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2HSV) # --- Masks --- # Background (yellow) range bg_mask = cv2.inRange(hsv, (15, 120, 120), (40, 255, 255)) # tune if needed # Shirt (blue) range – helpful for separate contrast if you want shirt_mask = cv2.inRange(hsv, (95, 80, 40), (130, 255, 255)) # Numbers “589” (white-ish areas on shirt) gray = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2GRAY) num_mask = cv2.threshold(gray, 210, 255, cv2.THRESH_BINARY)[1] # bright white # Jewelry (gold/yellow highlights) jew_mask = cv2.inRange(hsv, (12, 60, 120), (30, 255, 255)) # gold tones # Clean masks a bit def clean(m, k=3): kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (k,k)) m = cv2.morphologyEx(m, cv2.MORPH_OPEN, kernel, iterations=1) m = cv2.morphologyEx(m, cv2.MORPH_CLOSE, kernel, iterations=1) return m bg_mask = clean(bg_mask, 5) shirt_mask= clean(shirt_mask, 5) num_mask = clean(num_mask, 3) jew_mask = clean(jew_mask, 3) # --- Step 1: Replace background with deep charcoal --- out = img_bgr.copy() out[bg_mask>0] = SHADOW # --- Step 2: Convert subject to Casinofi duotone --- # Work on non-background regions subj = out.copy() subj_mask = (bg_mask==0).astype(np.uint8)*255 subj_gray = cv2.cvtColor(subj, cv2.COLOR_BGR2GRAY).astype(np.float32)/255.0 mapped = gradient_map(subj_gray).astype(np.uint8) mapped = cv2.bitwise_and(mapped, mapped, mask=subj_mask) bg_area = cv2.bitwise_and(out, out, mask=bg_mask) out = cv2.add(mapped, bg_area) # --- Step 3: Boost numbers “589” to brighter cream and keep edges crisp --- num_rgb = np.zeros_like(out, dtype=np.uint8) num_rgb[:] = HILITE_PLUS num_layer = cv2.bitwise_and(num_rgb, num_rgb, mask=num_mask) out = cv2.bitwise_and(out, out, mask=cv2.bitwise_not(num_mask)) out = cv2.add(out, num_layer) # Optional: thin dark stroke around numbers edges = cv2.Canny(num_mask, 50, 150) stroke = cv2.dilate(edges, np.ones((2,2), np.uint8), iterations=1) out[stroke>0] = (out[stroke>0]*0 + SHADOW*0.9).astype(np.uint8) # --- Step 4: Jewelry shine (Screen-like brighten in cream) --- # Create a cream layer and blend additively where jewelry mask is j_layer = np.zeros_like(out, dtype=np.float32) j_layer[:] = HILITE j_mask_f = (jew_mask.astype(np.float32)/255.0)[...,None] out_f = out.astype(np.float32) out = np.clip(out_f + j_layer*0.35*j_mask_f, 0, 255).astype(np.uint8) # --- Step 5: Gentle contrast pop on subject only --- subj_mask3 = cv2.merge([subj_mask, subj_mask, subj_mask]) subj_pix = np.where(subj_mask3>0) sub = out.astype(np.float32) sub[subj_pix] = np.clip((sub[subj_pix]-20)*1.08 + 20, 0, 255) out = sub.astype(np.uint8) # Save cv2.imwrite("output_casinofi.png", out) files.download("output_casinofi.png") print("Done. Download output_casinofi.png")

Using the input image, change the outer rim to a tarnished / aged rose gold colour, change 102 for a star in a tarnished / aged rose gold colour, and change Level 2 for Certified.

add blue back ligthing to the image

Using the uploaded photo, change the agree colour to bronze, and make sure all occurrences of 101 are replaced with 102.

light bronze and bronze, serene faces, sharp edges, high definition, contrast shading, realism

add that shiny sparkle overlay effect

turn into realistic bronze statue. cutout white background.

Coloriser cette image en utilisant le style de Frank Frazetta, le tatouage du modèle est dans les tons roses

Using the input image please generate a series of badges with different metals for the outer ring, one ring colour per image, leave everything else the same.

Make the picture with brighter colors

Make the outer rim bronze and replace any occurrence of 101 with 102.

generates exactly the same image but with better quality

Combine and sharpen the uploaded image. Brighten color and improve contrast

generates exactly the same image but with better quality