TROUBLESHOOTING.md

IndicDocParser: troubleshooting

Install and runtime problems, and what to do about them. The model card is README.md.

Nearly every install problem is the torch/torchvision/CUDA triangle.

Installing without the script, on Colab, Windows, or anywhere a shell script is awkward. These are the two commands install.sh runs:

pip install torch torchvision --index-url https://download.pytorch.org/whl/cu124   # your CUDA line
pip install -r requirements.txt

Keep torch and torchvision in that one command. torchvision pins an exact torch, so installing them separately lets pip pick a mismatched pair. A plain pip install torch also takes the newest wheel, currently CUDA 13, which on an older driver initialises to CPU with nothing but a warning. Use the index for your CUDA: cu121, cu124, cu128, cu130, or cpu.

ImportError after ImportError, or complaints that torchvision is too old. torchvision pins an exact torch, so if the two were installed separately pip may have paired them wrongly. Reinstall both in one command, from one index:

pip install --force-reinstall torch torchvision --index-url https://download.pytorch.org/whl/cu124

CUDA initialization: The NVIDIA driver on your system is too old, then everything runs on CPU. Plain pip install torch fetched a wheel built for a newer CUDA than your driver. Check with nvidia-smi, then reinstall from the matching index. Verify with:

import torch; print(torch.__version__, torch.cuda.is_available())

Qwen3VLVideoProcessor requires the Torchvision library. The recognizer needs torchvision; the layout stage does not. Install it together with torch, from the same index.

RTDetrHungarianMatcher requires the scipy library. You are on an old revision of this repo. Update to the current revision, which no longer builds the matcher during inference.