Update parallax.py

parallax.py

@@ -368,22 +368,7 @@ def convert_webp(image: Image.Image) -> str:
 def generate_animation_images(image, prompts=['make the eyes half-closed evenly; keep identity and all other details unchanged', 'make the eyes closed; keep identity and all other details unchanged'], target_size=1024, frame=None):
     rgba = np.asarray(image)
     face_results = FACE_YOLO.predict(source=Image.fromarray(np.asarray(Image.alpha_composite(Image.new('RGBA', image.size, (0, 0, 0)), image))[:, :, :3]), conf=0.5, iou=0.45, verbose=False, device='0' if torch.cuda.is_available() else 'cpu')
-    edited_outputs = []
     edited_images = []
-    filtered_prompts = []
-
-    if frame is None:
-        for prompt in prompts:
-            filtered_prompts.append(prompt)
-            edited_outputs.append(rgba.copy())
-
-    else:
-        for index, prompt in enumerate(prompts):
-            if frame == index:
-                filtered_prompts.append(prompt)
-                edited_outputs.append(rgba.copy())
-
-                break
 
     if len(face_results) > 0 and face_results[0].boxes is not None and len(face_results[0].boxes) > 0:
         min_x = np.iinfo(np.int32).max
@@ -391,6 +376,21 @@ def generate_animation_images(image, prompts=['make the eyes half-closed evenly;
         max_x = 0
         max_y = 0
         boxes = []
+        filtered_prompts = []
+        edited_outputs = []
+
+        if frame is None:
+            for prompt in prompts:
+                filtered_prompts.append(prompt)
+                edited_outputs.append(rgba.copy())
+
+        else:
+            for index, prompt in enumerate(prompts):
+                if frame == index:
+                    filtered_prompts.append(prompt)
+                    edited_outputs.append(rgba.copy())
+
+                    break
 
         for xyxy in np.round(face_results[0].boxes.xyxy.detach().cpu().numpy()).astype(np.int32):
             min_x = min(min_x, xyxy[0])
@@ -421,8 +421,8 @@ def generate_animation_images(image, prompts=['make the eyes half-closed evenly;
                 for x1, y1, x2, y2 in boxes:
                     edited_outputs[index][y1:y2, x1:x2, :3] = edited_rgb[y1 - min_y:y2 - min_y, x1 - min_x:x2 - min_x, :]
 
-    for edited_rgba in edited_outputs:
-        edited_images.append(convert_webp(Image.fromarray(edited_rgba, 'RGBA')))
+        for edited_rgba in edited_outputs:
+            edited_images.append(convert_webp(Image.fromarray(edited_rgba, 'RGBA')))
 
     return edited_images