115 lines
3.9 KiB
Python
115 lines
3.9 KiB
Python
import cv2
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import numpy as np
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import os
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import shutil
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def clean_ui_assets():
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# Paths to the newly generated UI artifacts (Solid Magenta #FF00FF usually)
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# I have to hunt them down by pattern again
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artifacts_dir = '/Users/davidkotnik/.gemini/antigravity/brain/07019d04-a214-43ab-9565-86f4e8f17e5b'
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mapping = {
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'ui_health_bar': 'health_bar.png',
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'ui_inventory_slot': 'inventory_slot.png',
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'ui_action_button': 'action_btn.png',
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'ui_dialog_box': 'dialog_panel.png'
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}
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# Destination in new project
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target_repo_dir = '/Users/davidkotnik/repos/novafarma/main/assets'
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target_project_dir = '/Users/davidkotnik/nova farma/main/assets'
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# Also copy to DEMO_FAZA1/UI if it exists?
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demo_ui_dir = '/Users/davidkotnik/repos/novafarma/assets/DEMO_FAZA1/UI'
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if not os.path.exists(demo_ui_dir):
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os.makedirs(demo_ui_dir, exist_ok=True)
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for key_pattern, dest_name in mapping.items():
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found_path = None
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# Find latest file matching pattern
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candidates = []
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for f in os.listdir(artifacts_dir):
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if key_pattern in f and f.endswith('.png'):
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candidates.append(os.path.join(artifacts_dir, f))
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if not candidates:
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print(f"Skipping {key_pattern} (not found)")
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continue
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# Sort by mtime to get latest
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candidates.sort(key=os.path.getmtime, reverse=True)
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found_path = candidates[0]
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print(f"Processing {found_path}")
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img = cv2.imread(found_path)
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if img is None:
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print("Failed to load")
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continue
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# Convert to BGRA
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img = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
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# Remove Magenta #FF00FF
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# OpenCV uses BGR: Magenta is (255, 0, 255) in BGR order
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# With tolerance just in case
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target = np.array([255, 0, 255])
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tol = 60 # strict-ish
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lower = np.clip(target - tol, 0, 255)
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upper = np.clip(target + tol, 0, 255)
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mask = cv2.inRange(img[:,:,:3], lower, upper)
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# Transparent wherever mask is true
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img[mask > 0, 3] = 0
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# Crop to content (non-transparent pixels)
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# Find bounding box of non-zero alpha
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alpha = img[:,:,3]
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coords = cv2.findNonZero(alpha)
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if coords is not None:
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x, y, w, h = cv2.boundingRect(coords)
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img = img[y:y+h, x:x+w]
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# Resize if massive? Generated images are likely 1024x1024
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# UI elements need to be manageable.
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# Health Bar: width 300?
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# Slot: 64x64 or 128x128?
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# Button: 128?
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# Panel: 400?
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h, w = img.shape[:2]
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new_w, new_h = w, h
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if 'health_bar' in dest_name and w > 400:
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scale = 400 / w
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new_w, new_h = int(w*scale), int(h*scale)
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elif 'inventory' in dest_name and w > 128:
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scale = 128 / w
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new_w, new_h = int(w*scale), int(h*scale)
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elif 'action' in dest_name and w > 140:
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scale = 128 / w
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new_w, new_h = int(w*scale), int(h*scale)
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elif 'dialog' in dest_name and w > 500:
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scale = 500 / w
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new_w, new_h = int(w*scale), int(h*scale)
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if new_w != w:
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img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_AREA)
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# Save to Main Assets
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dest_path = os.path.join(target_repo_dir, dest_name)
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cv2.imwrite(dest_path, img)
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print(f"Saved {dest_name} to {dest_path}")
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# Sync to demo folder
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shutil.copy2(dest_path, os.path.join(demo_ui_dir, dest_name))
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print(f"Synced to {demo_ui_dir}")
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# Sync to Project Folder
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shutil.copy2(dest_path, os.path.join(target_project_dir, dest_name))
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print(f"Synced to {target_project_dir}")
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if __name__ == "__main__":
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clean_ui_assets()
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