JoyCN/PaddleOCR-Pytorch

Weights

• ptocr_v5_server_det.safetensors — detection (server) weights [recommended]
• ptocr_v5_server_rec.safetensors — recognition (server) weights [recommended]
• ptocr_v5_server_det.pth — detection weights (legacy/compat)
• ptocr_v5_server_rec.pth — recognition weights (legacy/compat)

Configs

• PP-OCRv5_server_det.yml — detection model config
• PP-OCRv5_server_rec.yml — recognition model config

Download and load examples:

Python:

from huggingface_hub import hf_hub_download
import yaml

# Detection config
cfg_det_path = hf_hub_download("JoyCN/PaddleOCR-Pytorch", filename="PP-OCRv5_server_det.yml")
with open(cfg_det_path, "r", encoding="utf-8") as f:
    cfg_det = yaml.safe_load(f)

# Recognition config
cfg_rec_path = hf_hub_download("JoyCN/PaddleOCR-Pytorch", filename="PP-OCRv5_server_rec.yml")
with open(cfg_rec_path, "r", encoding="utf-8") as f:
    cfg_rec = yaml.safe_load(f)

Direct links (not counted by default):

• https://huggingface.co/JoyCN/PaddleOCR-Pytorch/resolve/main/PP-OCRv5_server_det.yml?download=true
• https://huggingface.co/JoyCN/PaddleOCR-Pytorch/resolve/main/PP-OCRv5_server_rec.yml?download=true

Download (recommended)

Python:

from huggingface_hub import hf_hub_download
from safetensors.torch import load_file

# Download safetensors
det_path = hf_hub_download("JoyCN/PaddleOCR-Pytorch", filename="ptocr_v5_server_det.safetensors")
rec_path = hf_hub_download("JoyCN/PaddleOCR-Pytorch", filename="ptocr_v5_server_rec.safetensors")

# Load state dicts
sd_det = load_file(det_path, device="cpu")
sd_rec = load_file(rec_path, device="cpu")

# Then
# model_det.load_state_dict(sd_det, strict=False)
# model_rec.load_state_dict(sd_rec, strict=False)

Direct links:

• https://huggingface.co/JoyCN/PaddleOCR-Pytorch/resolve/main/ptocr_v5_server_det.safetensors?download=true
• https://huggingface.co/JoyCN/PaddleOCR-Pytorch/resolve/main/ptocr_v5_server_rec.safetensors?download=true

Legacy (.pth) loading:

import torch
sd_det = torch.load("ptocr_v5_server_det.pth", map_location="cpu", weights_only=True)
if isinstance(sd_det, dict) and "state_dict" in sd_det: sd_det = sd_det["state_dict"]
sd_rec = torch.load("ptocr_v5_server_rec.pth", map_location="cpu", weights_only=True)
if isinstance(sd_rec, dict) and "state_dict" in sd_rec: sd_rec = sd_rec["state_dict"]
# model_det.load_state_dict(sd_det, strict=False)
# model_rec.load_state_dict(sd_rec, strict=False)

System Inference (predict_system.py)

Quick end-to-end OCR with PaddleOCR2Pytorch's system script.

1. Clone code and install minimal deps (CPU example)

git clone https://github.com/frotms/PaddleOCR2Pytorch.git
cd PaddleOCR2Pytorch
pip install -U torch opencv-python pillow pyyaml safetensors

2. Download weights and YAML (put in current folder)

# Weights (recommended)
curl -L -o ptocr_v5_server_det.safetensors   "https://huggingface.co/JoyCN/PaddleOCR-Pytorch/resolve/main/ptocr_v5_server_det.safetensors?download=true"
curl -L -o ptocr_v5_server_rec.safetensors   "https://huggingface.co/JoyCN/PaddleOCR-Pytorch/resolve/main/ptocr_v5_server_rec.safetensors?download=true"

# Configs (YAML)
curl -L -o PP-OCRv5_server_det.yml   "https://huggingface.co/JoyCN/PaddleOCR-Pytorch/resolve/main/PP-OCRv5_server_det.yml?download=true"
curl -L -o PP-OCRv5_server_rec.yml   "https://huggingface.co/JoyCN/PaddleOCR-Pytorch/resolve/main/PP-OCRv5_server_rec.yml?download=true"

3. Run end-to-end detection + recognition

python tools/infer/predict_system.py   --use_gpu False   --image_dir path/to/your_image.png   --det_algorithm DB   --det_yaml_path ./PP-OCRv5_server_det.yml   --rec_yaml_path ./PP-OCRv5_server_rec.yml   --det_model_path ./ptocr_v5_server_det.safetensors   --rec_model_path ./ptocr_v5_server_rec.safetensors   --rec_char_dict_path ./pytorchocr/utils/dict/ppocrv5_dict.txt   --rec_algorithm SVTR   --rec_image_shape "3,48,320"   --draw_img_save_dir ./inference_results

• Set --use_gpu True if you have a CUDA-ready environment.
• --rec_image_shape "3,48,320" is important for PP-OCRv5 recognition.
• Outputs: detection boxes, recognized text with scores, and a visualization image saved under --draw_img_save_dir.

Notes

• Prefer the huggingface_hub API (hf_hub_download/snapshot_download) for reliable downloads and caching.
• If needed, install safetensors: pip install safetensors.

Compatibility & Attribution

• Example inference uses the open-source PaddleOCR2Pytorch project (Apache-2.0): https://github.com/frotms/PaddleOCR2Pytorch.
• This repository is not affiliated with the PaddleOCR2Pytorch maintainers; please follow their license for code usage.

License

• This repository (weights and model card) is released under Apache-2.0.
• The referenced PaddleOCR2Pytorch codebase is also Apache-2.0.

Disclaimer

• Provided as-is, without warranties. Evaluate and validate for your use case.