This repo is a modified fork of AndreGuo/HDRTVDM, adapted for efficient ONNX inference on CPU-only environments. HDRTVDM is a deep learning model for converting LDR images into HDR outputs with BT.2020 precision and format flexibility.
- ✅ Updated
test.py
for Torch-CPU compatibility (no GPU required) - ✅ Added
export_onnx.py
for ONNX model export - ✅ Includes 3 pre-converted ONNX files for direct use
Before/After demo: https://whyb.github.io/HDRTVDM-onnx/
You can evaluate the enhancement quality by comparing the original SDR pictures with the HDR outputs generated by HDRTVDM:
Before (0_SDR) | After (0_HDR) |
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Before (1_SDR) | After (1_HDR) |
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Before (2_SDR) | After (2_HDR) |
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Before (3_SDR) | After (3_HDR) |
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Before (4_SDR) | After (4_HDR) |
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Before (5_SDR) | After (5_HDR) |
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Before (6_SDR) | After (6_HDR) |
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All demo files are included in this repo.
Coming soon — inference with ONNXRuntime will be supported.
python method/export_onnx.py --output export/TriSegNet.onnx --height 1080 --width 1920