import os import sys import subprocess # Disable SSR mode - it causes issues with Zero GPU os.environ["GRADIO_SSR_MODE"] = "false" # Check if we're running on HF Spaces with Zero GPU # HF Spaces sets SPACE_ID environment variable IS_HF_SPACE = bool(os.environ.get("SPACE_ID")) IS_ZERO_GPU = IS_HF_SPACE or os.environ.get("ZERO_GPU_MODE", "0") == "1" or os.environ.get("SPACES_ZERO_GPU", "0") == "1" if IS_HF_SPACE: print(f"🤗 Running on Hugging Face Space: {os.environ.get('SPACE_ID')}") # Try to import spaces for Zero GPU support # Note: spaces is provided by HF Spaces environment, not from pip try: import spaces HAS_SPACES = True print("✅ Spaces module available - Zero GPU support enabled") except ImportError: HAS_SPACES = False spaces = None print("ℹī¸ Spaces module not available - running without Zero GPU") import gradio as gr def _launch(): # Add CropFormer and DeepLab to PYTHONPATH (needed when using prebuilt detectron2) # Prebuilt detectron2 doesn't include projects/, so we need to add them manually repo_root = os.path.dirname(os.path.abspath(__file__)) projects_root = os.path.join(repo_root, "MaskClustering/third_party/detectron2/projects") # Add CropFormer (main project we use) cropformer_path = os.path.join(projects_root, "CropFormer") if cropformer_path not in sys.path: sys.path.insert(0, cropformer_path) # Add DeepLab (required by CropFormer for add_deeplab_config) deeplab_path = os.path.join(projects_root, "DeepLab") if deeplab_path not in sys.path: sys.path.insert(0, deeplab_path) # Set environment variables for Zero GPU optimization if IS_ZERO_GPU: print("🚀 Detected Zero GPU environment, optimizing settings...") os.environ["ZERO_GPU_MODE"] = "1" os.environ["MAX_GPU_MEMORY"] = "15GB" os.environ["BATCH_SIZE"] = "2" os.environ["MAX_IMAGES"] = "20" # Limit max images for Zero GPU os.environ["MAX_RESOLUTION"] = "512" # Lower resolution for memory optimization # Check if we need to install detectron2 and dependencies (first run only) # If using Dockerfile, DETECTRON2_INSTALLED is set and we skip compilation if not os.environ.get("DETECTRON2_INSTALLED"): print("🔧 Installing CropFormer dependencies...") # Check if pytorch3d is already installed (from Dockerfile prebuild) pytorch3d_installed = False try: import pytorch3d pytorch3d_installed = True print(f"✅ pytorch3d already installed (version: {getattr(pytorch3d, '__version__', 'unknown')})") except ImportError: pass try: # Install setuptools first (needed for mmcv build) subprocess.check_call([ sys.executable, "-m", "pip", "install", "setuptools<81" ]) # Install CropFormer/Mask2Former dependencies # Use --no-build-isolation to use system setuptools with pkg_resources subprocess.check_call([ sys.executable, "-m", "pip", "install", "--no-build-isolation", "mmcv>=1.4.0,<2.0.0" ]) # Only install pytorch3d if not already installed if not pytorch3d_installed: # Try prebuilt wheel first (much faster than compiling) # Using third-party wheels from https://github.com/MiroPsota/torch_packages_builder print("🔧 Installing pytorch3d from prebuilt wheel...") try: subprocess.check_call([ sys.executable, "-m", "pip", "install", "--extra-index-url", "https://miropsota.github.io/torch_packages_builder", "pytorch3d" ]) print("✅ pytorch3d installed from prebuilt wheel!") except subprocess.CalledProcessError: # Fallback to compiling from source if prebuilt wheel not available print("⚠ī¸ Prebuilt wheel not found, compiling from source...") cuda_env = { **os.environ, "FORCE_CUDA": "1", "TORCH_CUDA_ARCH_LIST": "7.5;8.0;8.6;8.9;9.0", } subprocess.check_call([ sys.executable, "-m", "pip", "install", "--no-build-isolation", "git+https://github.com/facebookresearch/pytorch3d.git" ], env=cuda_env) print("✅ CropFormer dependencies installed!") # Check if detectron2 is already installed (from Dockerfile prebuild) detectron2_installed = False try: import detectron2 detectron2_installed = True print(f"✅ detectron2 already installed (version: {getattr(detectron2, '__version__', 'unknown')})") except ImportError: pass if not detectron2_installed: # Use prebuilt wheels from https://miropsota.github.io/torch_packages_builder # This is MUCH faster than compiling from source (~5s vs ~60s) print("🔧 Installing detectron2 from prebuilt wheel...") try: subprocess.check_call([ sys.executable, "-m", "pip", "install", "--extra-index-url", "https://miropsota.github.io/torch_packages_builder", "detectron2" ]) print("✅ detectron2 installed from prebuilt wheel!") except subprocess.CalledProcessError: # Fallback to compiling from vendored source print("⚠ī¸ Prebuilt wheel not found, compiling from vendored source...") cuda_env = { **os.environ, "FORCE_CUDA": "1", "TORCH_CUDA_ARCH_LIST": "7.5;8.0;8.6;8.9;9.0", } subprocess.check_call([ sys.executable, "-m", "pip", "install", "--no-build-isolation", "-e", "MaskClustering/third_party/detectron2" ], env=cuda_env) print("✅ detectron2 compiled and installed!") # Install MSDeformAttn from prebuilt wheel print("🔧 Installing MultiScaleDeformableAttention from prebuilt wheel...") try: subprocess.check_call([ sys.executable, "-m", "pip", "install", "--extra-index-url", "https://miropsota.github.io/torch_packages_builder", "MultiScaleDeformableAttention" ]) print("✅ MultiScaleDeformableAttention installed from prebuilt wheel!") except subprocess.CalledProcessError: # Fallback to compiling from source print("⚠ī¸ Prebuilt wheel not found, compiling MSDeformAttn from source...") repo_root = os.path.dirname(os.path.abspath(__file__)) cropformer_root = os.path.join(repo_root, "MaskClustering/third_party/detectron2/projects/CropFormer") ops_dir = os.path.join(cropformer_root, "mask2former/modeling/pixel_decoder/ops") if 'cuda_env' not in locals(): cuda_env = { **os.environ, "FORCE_CUDA": "1", "TORCH_CUDA_ARCH_LIST": "7.5;8.0;8.6;8.9;9.0", } subprocess.check_call( [sys.executable, "-m", "pip", "install", "-e", ".", "--no-build-isolation"], cwd=ops_dir, env=cuda_env ) print("✅ MSDeformAttn compiled and installed!") # Compile entity_api PythonAPI (still needed, but fast) repo_root = os.path.dirname(os.path.abspath(__file__)) cropformer_root = os.path.join(repo_root, "MaskClustering/third_party/detectron2/projects/CropFormer") print("🔧 Compiling entity_api PythonAPI...") entity_api_dir = os.path.join(cropformer_root, "entity_api/PythonAPI") if os.path.exists(entity_api_dir): try: subprocess.check_call(["make"], cwd=entity_api_dir, shell=True) print("✅ entity_api compiled successfully!") except subprocess.CalledProcessError as e: print(f"⚠ī¸ entity_api compilation failed (non-critical): {e}") else: print(f"⚠ī¸ entity_api directory not found: {entity_api_dir}") print("🔄 Restarting to load detectron2...") # Set environment variable to avoid reinstalling on restart os.environ["DETECTRON2_INSTALLED"] = "1" # Restart the script os.execv(sys.executable, [sys.executable] + sys.argv) except subprocess.CalledProcessError as e: print(f"❌ Failed to install dependencies: {e}") raise else: # Second run: verify imports work print("🔍 Verifying detectron2 and mmcv imports...") try: import detectron2 import mmcv print(f"✅ detectron2 available (version: {getattr(detectron2, '__version__', 'unknown')})") print(f"✅ mmcv available (version: {getattr(mmcv, '__version__', 'unknown')})") except ImportError as e: print(f"❌ Required module cannot be imported: {e}") print(f" sys.path: {sys.path}") raise # HF Spaces/Gradio sometimes calls /api_info regardless of `show_api=False`. # Some gradio_client versions crash when JSON schema uses boolean `additionalProperties`. # Patch defensively to avoid bringing down the whole app. try: import gradio_client.utils as _gcu if hasattr(_gcu, "_json_schema_to_python_type"): _orig = _gcu._json_schema_to_python_type def _json_schema_to_python_type_patched(schema, defs=None): if isinstance(schema, bool): return "Any" return _orig(schema, defs) _gcu._json_schema_to_python_type = _json_schema_to_python_type_patched except Exception: pass # HF Spaces expects the app to listen on 0.0.0.0:7860 (PORT may be provided). import mvp port = int(os.getenv("PORT", "7860")) # `mvp` defines `demo` (gr.Blocks). We launch it here instead of inside `mvp.py`. mvp.demo.queue(max_size=20).launch( server_name="0.0.0.0", server_port=port, show_error=True, share=False, show_api=False, ) if __name__ == "__main__": _launch()