Create requirements.txt

requirements.txt

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+# ══════════════════════════════════════════════════════════════════════════════
+# Blueprint Room Extractor — requirements.txt
+# Target: Hugging Face Spaces (NVIDIA T4 / A10G GPU runtime)
+#
+# Install order matters — torch must come before torchvision/torchaudio and
+# before segment-anything / easyocr so they all link against the same libcuda.
+#
+# To run locally with GPU:
+#   pip install -r requirements.txt
+#
+# To run locally CPU-only (fallback):
+#   pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cpu
+# ══════════════════════════════════════════════════════════════════════════════
+
+# ── Web framework ─────────────────────────────────────────────────────────────
+flask>=3.0.0
+werkzeug>=3.0.0
+
+# ── Core numerics ─────────────────────────────────────────────────────────────
+numpy>=1.26.0,<3.0
+scipy>=1.12.0
+scikit-image>=0.22.0
+pillow>=10.0.0
+
+# ── OpenCV (CUDA-enabled build via headless + contrib) ────────────────────────
+# opencv-python-headless is the standard HF Spaces variant (no GTK/Qt deps).
+# The opencv-contrib-python-headless build ships ximgproc (thinning) and
+# cuda* modules when the underlying system has libcuda.so.
+# On CPU-only machines both packages fall back gracefully; cv2.cuda
+# functions will raise RuntimeError which we catch and route to CPU.
+opencv-contrib-python-headless>=4.9.0.80
+
+# ── PyTorch — CUDA 12.1 wheel (HF Spaces default CUDA version) ───────────────
+# HF Spaces hardware: NVIDIA T4 (sm_75) or A10G (sm_86), CUDA 12.x
+torch>=2.3.0
+torchvision>=0.18.0
+torchaudio>=2.3.0
+
+# ── CuPy — GPU NumPy (matches CUDA 12.x on HF Spaces) ────────────────────────
+# Provides cp.asarray / cp.asnumpy for zero-copy GPU↔CPU transfers and
+# replaces NumPy hotspots (chroma erase, RLE encoding, gap analysis) on GPU.
+cupy-cuda12x>=13.0.0
+
+# ── Segment Anything Model (SAM) ──────────────────────────────────────────────
+# Facebook's original SAM — predictor.predict() runs on CUDA when available.
+# Checkpoint (vit_h ~2.4 GB) is downloaded at runtime from HF Hub.
+git+https://github.com/facebookresearch/segment-anything.git
+
+# ── OCR — EasyOCR with GPU support ───────────────────────────────────────────
+# EasyOCR uses its own torch-based CRNN; when torch.cuda.is_available() it
+# automatically moves tensors to GPU without any code change.
+easyocr>=1.7.1
+
+# ── ONNXRuntime GPU (optional accelerator for EasyOCR detection backbone) ─────
+# EasyOCR's detection model can run via onnxruntime-gpu if present.
+onnxruntime-gpu>=1.18.0
+
+# ── Hugging Face integration ──────────────────────────────────────────────────
+# huggingface_hub: model download (SAM checkpoint)
+# spaces: @spaces.GPU decorator for zero-GPU billing on HF Spaces free tier
+huggingface_hub>=0.23.0
+spaces>=0.29.0
+
+# ── Enchant spell checker (room-label validation) ─────────────────────────────
+# Requires system package: apt-get install libenchant-2-dev (add to packages.txt)
+pyenchant>=3.2.2
+
+# ── Miscellaneous utilities ───────────────────────────────────────────────────
+# imageio: used by skimage internally
+imageio>=2.34.0
+# tqdm: progress bars inside EasyOCR / SAM
+tqdm>=4.66.0
+# requests: SAM checkpoint download fallback
+requests>=2.31.0