Create bootstrap.py

bootstrap.py

@@ -0,0 +1,50 @@
+#!/usr/bin/env python3
+# Bootstrap file for SEEM on Hugging Face Spaces
+
+import os
+import sys
+import subprocess
+
+print("Setting up SEEM environment...")
+
+# Install detectron2 first (before other imports)
+print("Installing detectron2...")
+os.system("pip install -q git+https://github.com/MaureenZOU/detectron2-xyz.git")
+
+# Set Python path to include the repository root
+os.environ["PYTHONPATH"] = os.getcwd()
+print(f"Set PYTHONPATH to: {os.getcwd()}")
+
+# Create a patched version of app.py with CPU support
+app_path = "app.py"
+app_patched_path = "app_patched.py"
+
+with open(app_path, "r") as f:
+    app_code = f.read()
+
+# Replace the device setup code to work with either CPU or GPU
+app_code = app_code.replace(
+    "model = BaseModel(opt, build_model(opt)).from_pretrained(pretrained_pth).eval().cuda()",
+    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n"
+    "print(f\"Using device: {device}\")\n"
+    "model = BaseModel(opt, build_model(opt)).from_pretrained(pretrained_pth).eval().to(device)"
+)
+
+# Replace the inference function to handle both CPU and GPU
+app_code = app_code.replace(
+    "@torch.no_grad()\ndef inference(image, task, *args, **kwargs):\n    with torch.autocast(device_type='cuda', dtype=torch.float16):",
+    "@torch.no_grad()\ndef inference(image, task, *args, **kwargs):\n    if torch.cuda.is_available():\n        with torch.autocast(device_type='cuda', dtype=torch.float16):"
+)
+
+# Add CPU fallback to the inference function
+app_code = app_code.replace(
+    "        if 'Video' in task:\n            return interactive_infer_video(model, audio, image, task, *args, **kwargs)\n        else:\n            return interactive_infer_image(model, audio, image, task, *args, **kwargs)",
+    "        if 'Video' in task:\n            return interactive_infer_video(model, audio, image, task, *args, **kwargs)\n        else:\n            return interactive_infer_image(model, audio, image, task, *args, **kwargs)\n    else:\n        # Run without autocast on CPU\n        if 'Video' in task:\n            return interactive_infer_video(model, audio, image, task, *args, **kwargs)\n        else:\n            return interactive_infer_image(model, audio, image, task, *args, **kwargs)"
+)
+
+with open(app_patched_path, "w") as f:
+    f.write(app_code)
+
+# Run the patched app
+print("Starting SEEM demo...")
+os.system(f"python {app_patched_path}")