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8071fe61c5
* feat(shared): add enhance-faces tool definition and i18n strings * feat(ai): add face enhancement script with GFPGAN and CodeFormer support Detects faces via MediaPipe dual-model approach, then enhances using GFPGAN (proven) or CodeFormer (via codeformer-pip) with auto fallback. Supports strength-based alpha blending with original image. * feat(ai): add TypeScript bridge for face enhancement * feat(api): add enhance-faces route with GFPGAN/CodeFormer support * feat(web): add enhance-faces settings component and register in tool registry * feat(docker): add CodeFormer dependency and model download - Add codeformer-pip to both CPU and GPU requirements - Download CodeFormer model (~375MB) at Docker build time - Add CodeFormer to smoke test verification * fix(enhance-faces): address code review findings - Skip alpha blend for CodeFormer (strength already applied via fidelity weight) - Hide "only enhance main face" checkbox when Best (CodeFormer) is selected - Fix sensitivity slider labels (swap More/Fewer faces to match actual behavior) - Register EnhanceFacesControls in pipeline step settings - Remove model names from user-facing descriptions * fix(enhance-faces): fix CodeFormer integration and Docker setup - Add codeformer-pip install to Dockerfile with --no-deps to avoid numpy 2.x conflict - Re-pin numpy==1.26.4 after codeformer-pip install - Pin codeformer-pip==0.0.4 in requirements files - Broaden auto-mode fallback to catch any Exception from CodeFormer --------- Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
11 lines
201 B
Plaintext
11 lines
201 B
Plaintext
rembg==2.0.62
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realesrgan==0.3.0
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paddleocr==2.9.1
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paddlepaddle-gpu==3.0.0
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mediapipe==0.10.21
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onnxruntime-gpu==1.20.1
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numpy==1.26.4
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Pillow==11.1.0
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opencv-python-headless==4.10.0.84
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codeformer-pip==0.0.4
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