AnhP/DJCM-Test
By AnhP · ↓ 0 · ♥ 4 · Updated 2025-09-20
What's in this repo
This page lists the files in AnhP/DJCM-Test, including djcm.onnx, djcm_fp16.onnx and more.
- 6 ONNX models (.onnx files)
- 75 files, including 42 .pt, 18 .json, 6 .onnx, 5 .txt, 2 .md, 1 .zip
- Last updated 2025-09-20
ONNX files
| File | Size | Download |
|---|---|---|
| 10738/djcm.onnx | — | Download |
| 10738/djcm_fp16.onnx | — | Download |
| Training With Mixed Dataset/djcm.onnx | — | Download |
| Training With Mixed Dataset/djcm_fp16.onnx | — | Download |
| djcm.onnx | — | Download |
| djcm_fp16.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
The model consumes a lot of resources for inference, so its inference code was modified to split the input into smaller parts, which results in longer inference time.
The model might not have been fully trained, so the quality may not be optimal. It is currently paused at checkpoint 22080.
The djcm.pt model has been trimmed by removing to_wav since it is not used.
Training with the original DJCM code (WIN LENGTH 2048 and HOP LENGTH 320)
| index | sdr±std | gnsdr | rpa±std | rca±std | oa±std |
|---|---|---|---|---|---|
| 414 | 5.83±2.09 | 2.82 | 81.52±13.59 | 84.06±10.77 | 78.85±10.99 |
| 828 | 7.78±1.86 | 4.77 | 90.73±7.32 | 91.91±6.13 | 88.2±6.61 |
| 1242 | 8.67±1.71 | 5.65 | 90.65±7.33 | 91.37±6.3 | 89.57±6.09 |
| 1656 | 8.94±1.82 | 5.92 | 92.65±5.61 | 93.14±5.09 | 87.16±6.68 |
| 2484 | 10.16±2.05 | 7.15 | 92.17±5.9 | 92.42±5.67 | 91.04±5.16 |
| 2898 | 10.03±1.92 | 7.02 | 92.74±5.74 | 93.08±5.57 | 89.4±5.59 |
| 3312 | 10.56±1.83 | 7.55 | 92.85±5.57 | 93.18±5.25 | 91.85±4.82 |
| 4554 | 11.28±2.19 | 8.27 | 93.57±5.42 | 93.81±5.18 | 92.07±4.62 |
| 5796 | 11.27±2.06 | 8.25 | 93.59±5.53 | 93.97±5.0 | 91.65±5.08 |
| 6624 | 11.57±2.05 | 8.56 | 93.86±5.16 | 94.04±4.98 | *92.93±4.26 |
| 7038 | 11.63±1.98 | 8.62 | 94.05±4.82 | 94.29±4.44 | 91.79±4.63 |
| 7452 | 11.0±1.88 | 7.99 | 93.43±5.39 | 93.68±4.89 | 91.48±5.16 |
| 7866 | 11.55±2.22 | 8.54 | 93.15±5.43 | 93.37±5.14 | 91.62±4.88 |
| 8280 | 11.76±2.2 | 8.75 | 93.7±5.26 | 93.88±4.99 | 92.62±4.35 |
| 8694 | *12.25±2.16 | *9.23 | 93.32±5.45 | 93.49±5.15 | 92.55±4.3 |
| 9086 | 9.13±1.34 | 6.12 | 94.76±4.0 | 95.16±3.56 | 70.17±9.26 |
| 9499 | 8.75±1.19 | 5.74 | 95.06±3.76 | 95.49±3.4 | 71.86±9.23 |
| 9912 | 9.16±1.16 | 6.15 | 95.48±3.68 | 95.73±3.46 | 73.65±8.35 |
| 10325 | 8.66±0.97 | 5.65 | 95.35±3.6 | 95.72±3.06 | 74.58±7.88 |
| 10738 | 8.2±0.85 | 5.19 | *95.58±3.52 | *95.87±3.23 | 75.25±7.87 |
Training with my modified DJCM code (WIN LENGTH 1024 and HOP LENGTH 160) With a mixture of 5 datasets, each set is extracted 20% for testing.
| index | sdr±std | gnsdr | rpa±std | rca±std | oa±std |
|---|---|---|---|---|---|
| 11776 | NONE | NONE | 88.87±7.25 | 89.9±6.74 | 34.2±22.21 |
| 14720 | NONE | NONE | 89.09±7.47 | 90.15±6.88 | 39.83±24.26 |
| 17664 | NONE | NONE | 89.47±7.16 | 90.44±6.65 | 37.56±25.77 |
| 20608 | NONE | NONE | 90.49±6.63 | 91.29±6.24 | 37.71±25.67 |
| 22080 | NONE | NONE | *90.65±6.69 | *91.56±6.15 | *41.01±24.69 |
Training Dataset: https://huggingface.co/datasets/AnhP/Mir-1k-use-DJCM-training/resolve/main/dataset.zip
Inference Code: https://github.com/PhamHuynhAnh16/DJCM/blob/main/inference.py
Training Code: https://github.com/PhamHuynhAnh16/DJCM/blob/main/train.py
Export Small Code: https://github.com/PhamHuynhAnh16/DJCM/blob/main/export_small_model.py
Export Onnx Code: https://github.com/PhamHuynhAnh16/DJCM/blob/main/export_onnx.py
Model info
Created: 2025-07-15
Updated: 2025-09-20
View on Hugging FaceFiles (75)
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