feat: Integrated Stream asset and Kai animation system

2026-01-29 00:09:00 +01:00
parent 94565adffc
commit afa0e3c662
59 changed files with 1477 additions and 19 deletions
--- a/scripts/deploy_hud_extras.py
+++ b/scripts/deploy_hud_extras.py
@@ -0,0 +1,80 @@
+import cv2
+import numpy as np
+import os
+import shutil
+
+def deploy_hud_extras():
+    artifacts_dir = '/Users/davidkotnik/.gemini/antigravity/brain/07019d04-a214-43ab-9565-86f4e8f17e5b'
+    
+    mapping = {
+        'ui_minimap_frame': 'minimap_frame.png',
+        'ui_weather_icons': 'weather_icons_sheet.png',
+        'ui_weather_widget_retry': 'weather_widget.png'
+    }
+    
+    targets = [
+        '/Users/davidkotnik/repos/novafarma/main/assets',
+        '/Users/davidkotnik/repos/novafarma/assets/DEMO_FAZA1/UI',
+        '/Users/davidkotnik/nova farma/main/assets'
+    ]
+    for t in targets:
+        os.makedirs(t, exist_ok=True)
+
+    for key_pattern, dest_name in mapping.items():
+        # Find latest file
+        candidates = []
+        for f in os.listdir(artifacts_dir):
+            if key_pattern in f and f.endswith('.png'):
+                candidates.append(os.path.join(artifacts_dir, f))
+        
+        if not candidates:
+            print(f"Skipping {key_pattern}")
+            continue
+            
+        candidates.sort(key=os.path.getmtime, reverse=True)
+        found_path = candidates[0]
+        
+        print(f"Processing {found_path}")
+        img = cv2.imread(found_path)
+        if img is None: continue
+            
+        # BG Removal
+        img = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
+        target = np.array([255, 0, 255]) 
+        tol = 60 
+        lower = np.clip(target - tol, 0, 255)
+        upper = np.clip(target + tol, 0, 255)
+        mask = cv2.inRange(img[:,:,:3], lower, upper)
+        img[mask > 0, 3] = 0
+        
+        # Crop Content
+        coords = cv2.findNonZero(img[:,:,3])
+        if coords is not None:
+            x, y, w, h = cv2.boundingRect(coords)
+            img = img[y:y+h, x:x+w]
+        
+        # Resize Logic
+        h, w = img.shape[:2]
+        new_w, new_h = w, h
+        
+        if 'minimap' in dest_name and w > 256:
+             scale = 256 / w
+             new_w, new_h = int(w*scale), int(h*scale)
+        elif 'widget' in dest_name and w > 256:
+             scale = 256 / w
+             new_w, new_h = int(w*scale), int(h*scale)
+        elif 'icons' in dest_name and w > 512:
+             scale = 512 / w
+             new_w, new_h = int(w*scale), int(h*scale)
+
+        if new_w != w:
+             img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_AREA)
+
+        # Distribute
+        for t in targets:
+            final_path = os.path.join(t, dest_name)
+            cv2.imwrite(final_path, img)
+            print(f"Saved to {final_path}")
+
+if __name__ == "__main__":
+    deploy_hud_extras()