add sam2

app.py

@@ -50,24 +50,6 @@ def install_sam2():
             # 以可编辑模式安装SAM2
             subprocess.run(["pip", "install", "-e", "."], check=True)
             
-            # 切换到checkpoints目录下载模型
-            os.chdir("checkpoints")
-            if not os.path.exists("download_ckpts.sh"):
-                subprocess.run([
-                    "wget", 
-                    "https://raw.githubusercontent.com/facebookresearch/sam2/main/checkpoints/download_ckpts.sh"
-                ], check=True)
-                subprocess.run(["chmod", "+x", "download_ckpts.sh"], check=True)
-            
-            # 下载检查点（添加超时和重试）
-            result = subprocess.run(["./download_ckpts.sh"], check=False)
-            if result.returncode != 0:
-                print("Warning: Checkpoint download failed, trying alternative method...")
-                subprocess.run([
-                    "wget",
-                    "https://dl.fbaipublicfiles.com/sam2/sam2.1_hiera_large.pt",
-                    "-O", "sam2.1_hiera_large.pt"
-                ], check=True)
             
         except Exception as e:
             print(f"Error during SAM2 installation: {str(e)}")
@@ -94,7 +76,7 @@ print("🎉 SAM2 modules imported successfully!")
 # ------------------ 初始化模型 ------------------
 # 使用相对路径
 MODEL_PATH = "geshang/Seg-R1-COD"
-SAM_CHECKPOINT = "third_party/sam2/checkpoints/sam2.1_hiera_large.pt"
+SAM_CHECKPOINT = "sam2_weights/sam2.1_hiera_large.pt"
 
 # 自动检测设备
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
@@ -123,8 +105,8 @@ class CustomSAMWrapper:
             from sam2.sam2_image_predictor import SAM2ImagePredictor
             
             self.device = torch.device(device)
-            model_cfg = os.path.join("third_party/sam2", "configs/sam2.1/sam2.1_hiera_l.yaml")
-            sam_model = build_sam2(model_cfg, model_path)
+            # model_cfg = os.path.join("third_party/sam2", "configs/sam2.1/sam2.1_hiera_l.yaml")
+            sam_model = build_sam2("configs/sam2.1/sam2.1_hiera_l.yaml", model_path)
             sam_model = sam_model.to(self.device)
             self.predictor = SAM2ImagePredictor(sam_model)
             self.last_mask = None

sam2_weights/sam2.1_hiera_large.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2647878d5dfa5098f2f8649825738a9345572bae2d4350a2468587ece47dd318
+size 898083611