Update app.py

app.py

@@ -8,21 +8,11 @@ import numpy as np
 import spaces
 from omegaconf import OmegaConf
 from huggingface_hub import snapshot_download
-from PIL import Image
 
 REPO_DIR = snapshot_download(repo_id="Hang2991/PICS")
 os.chdir(REPO_DIR)
 sys.path.insert(0, REPO_DIR)
 sys.path.insert(0, os.path.join(REPO_DIR, "dinov2"))
-sys.path.insert(0, os.path.join(REPO_DIR, "sample"))
-
-
-import shutil
-# 1. 强制把 sample 文件夹拷贝到 Gradio 运行的根目录 (/home/user/app)
-# 不管你 chdir 去了哪，这一步保证了 /home/user/app/sample 真实存在
-if not os.path.exists("/home/user/app/sample"):
-    # REPO_DIR 是你下载的那个缓存路径
-    shutil.copytree(os.path.join(REPO_DIR, "sample"), "/home/user/app/sample")
 
 from cldm.model import create_model, load_state_dict
 from cldm.ddim_hacked import DDIMSampler
@@ -32,7 +22,6 @@ model = create_model(config.config_file).cpu()
 model.load_state_dict(load_state_dict(config.pretrained_model, location='cpu'))
 model.eval()
 
-
 def get_input(batch, k):
     x = batch[k]
     if len(x.shape) == 3:
@@ -104,31 +93,15 @@ def pics_pairwise_inference(background, img_a, mask_a, img_b, mask_b):
     device = "cuda"
     model.to(device)
     ddim_sampler = DDIMSampler(model)
-
-    def force_to_pil(data):
-        if data is None: return None
-        if isinstance(data, str): # 如果是路径字符串
-            return Image.open(data).convert("RGB")
-        if isinstance(data, np.ndarray): # 如果已经是 numpy
-            return Image.fromarray(data).convert("RGB")
-        return data.convert("RGB") # 假设是 PIL
-
-    background = force_to_pil(background)
-    img_a = force_to_pil(img_a)
-    mask_a = force_to_pil(mask_a)
-    img_b = force_to_pil(img_b)
-    mask_b = force_to_pil(mask_b)
-    
     back_image = np.array(background)
-    # back_image = np.array(background)
     
     item_with_collage = {}
-    # objs = [(img_a, mask_a), (img_b, mask_b)]
-    # for j, (img, mask) in enumerate(objs):
-    #     temp_patch = f"temp_obj_{j}.png"
-    #     cv2.imwrite(temp_patch, cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR))
-    #     tar_mask = (np.array(mask)[:, :, 0] > 128).astype(np.uint8)
-    #     item_with_collage.update(process_pairs_multiple(tar_mask, back_image, temp_patch, counter=j))
+    objs = [(img_a, mask_a), (img_b, mask_b)]
+    for j, (img, mask) in enumerate(objs):
+        temp_patch = f"temp_obj_{j}.png"
+        cv2.imwrite(temp_patch, cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR))
+        tar_mask = (np.array(mask)[:, :, 0] > 128).astype(np.uint8)
+        item_with_collage.update(process_pairs_multiple(tar_mask, back_image, temp_patch, counter=j))
 
     item_with_collage = process_composition(item_with_collage, obj_thr=2)
 
@@ -210,19 +183,17 @@ with gr.Blocks(title="PICS: Pairwise Spatial Compositing with Spatial Interactio
     # --- 核心修改：把 Examples 放在这里 ---
     gr.Markdown("### 💡 Quick Examples")
     gr.Examples(
-    examples=[
+        examples=[
             [
-                "/home/user/app/sample/bread_basket/image.jpg", 
-                "/home/user/app/sample/bread_basket/object_0.png", 
-                "/home/user/app/sample/bread_basket/object_0_mask.png", 
-                "/home/user/app/sample/bread_basket/object_1.png", 
-                "/home/user/app/sample/bread_basket/object_1_mask.png"
+                "sample/bread_basket/image.jpg", 
+                "sample/bread_basket/object_0.png", "sample/bread_basket/object_0_mask.png", 
+                "sample/bread_basket/object_1.png", "sample/bread_basket/object_1_mask.png"
             ]
         ],
         inputs=[bg_input, obj_a_img, obj_a_mask, obj_b_img, obj_b_mask],
         outputs=output_img,   # 现在它认识这个变量了
         fn=pics_pairwise_inference, 
-        cache_examples=False, 
+        cache_examples=True, 
     )
 
     # 按钮绑定