Update app.py

app.py

@@ -14,8 +14,7 @@ import cv2
 from typing import List, Tuple, Optional
 import sys
 
-# ------------------ 安装SAM2依赖 ------------------
-# ------------------ 修复SAM2模块路径问题 ------------------
+
 def add_sam2_to_path():
     """将SAM2安装目录添加到Python路径"""
     sam2_dir = os.path.abspath("third_party/sam2")
@@ -23,7 +22,6 @@ def add_sam2_to_path():
         sys.path.insert(0, sam2_dir)
     return sam2_dir
 
-# ------------------ 安装SAM2依赖 ------------------
 def install_sam2():
     """检查并安装SAM2及其依赖"""
     sam2_dir = "third_party/sam2"
@@ -31,7 +29,6 @@ def install_sam2():
         print("Installing SAM2...")
         os.makedirs("third_party", exist_ok=True)
         
-        # 克隆仓库（添加--recursive以防有子模块）
         subprocess.run([
             "git", "clone", 
             "--recursive", 
@@ -39,15 +36,10 @@ def install_sam2():
             sam2_dir
         ], check=True)
         
-        # 切换到sam2目录安装
         original_dir = os.getcwd()
         try:
             os.chdir(sam2_dir)
-            
-            # 先安装核心依赖
-            # subprocess.run(["pip", "install", "-r", "requirements.txt"], check=True)
-            
-            # 以可编辑模式安装SAM2
+    
             subprocess.run(["pip", "install", "-e", "."], check=True)
             
             
@@ -62,27 +54,21 @@ def install_sam2():
         print("SAM2 already exists, skipping installation.")
 
 
-    # 1. 安装SAM2
 install_sam2()
 
-# 2. 确保路径正确
 sam2_dir = add_sam2_to_path()
 
-# 3. 现在可以安全导入SAM2模块
 from sam2.build_sam import build_sam2
 from sam2.sam2_image_predictor import SAM2ImagePredictor
 print("🎉 SAM2 modules imported successfully!")
 
-# ------------------ 初始化模型 ------------------
-# 使用相对路径
+
 MODEL_PATH = "geshang/Seg-R1-COD"
 SAM_CHECKPOINT = "sam2_weights/sam2.1_hiera_large.pt"
 
-# 自动检测设备
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 RESIZE_SIZE = (768, 768)
 
-# 加载Qwen模型
 try:
     model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
         MODEL_PATH,
@@ -93,7 +79,6 @@ try:
     print(f"Qwen model loaded on {DEVICE}")
 except Exception as e:
     print(f"Error loading Qwen model: {e}")
-    # 创建虚拟模型以便继续运行
     model = None
     processor = None
 
@@ -145,10 +130,8 @@ class CustomSAMWrapper:
             print(f"SAM prediction error: {e}")
             return np.zeros((image.height, image.width), dtype=bool), 0.0
 
-# 初始化SAM包装器
 sam_wrapper = CustomSAMWrapper(SAM_CHECKPOINT, device=DEVICE)
 
-# ------------------ 推理相关函数 ------------------
 
 def parse_custom_format(content: str):
     point_pattern = r"<points>\s*(\[\s*(?:\[\s*\d+\s*,\s*\d+\s*\]\s*,?\s*)+\])\s*</points>"
@@ -331,7 +314,6 @@ def run_pipeline(image: PILImage.Image, prompt: str):
         print(f"Pipeline error: {e}")
         return f"Error processing request: {str(e)}", None
 
-# ------------------ 启动 Gradio ------------------
 
 with gr.Blocks(title="Seg-R1") as demo:
     gr.Markdown("# Seg-R1: Visual Segmentation Assistant")