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.gitattributes

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README.md

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+---
+language:
+- vi
+license: agpl-3.0
+library_name: ultralytics
+pipeline_tag: object-detection
+tags:
+- yolo
+- yolov8
+- onnx
+- torchscript
+- tensorrt
+- int8
+- fp16
+- vision
+- object-detection
+- traffic-sign
+- vietnam
+---
+
+# VTSR
+
+VTSR is a YOLOv8n object-detection model for recognizing 56 classes of Vietnamese traffic signs.
+
+This repository focuses on optimized deployment artifacts derived from the original FP32 PyTorch checkpoint, including ONNX INT8, TensorRT INT8, and TorchScript FP16 models.
+
+## Demo
+
+An interactive Gradio demo is available on Hugging Face Spaces:
+
+https://huggingface.co/spaces/liamxdev/vtsr-demo
+
+The demo currently uses the ONNX INT8 artifact for CPU-compatible inference.
+
+## Model details
+
+| Property           | Value                           |
+| ------------------ | ------------------------------- |
+| Task               | Object detection                |
+| Architecture       | YOLOv8n                         |
+| Classes            | 56                              |
+| Input size         | 640 × 640                       |
+| Label descriptions | `label-mapping.json`            |
+| Dataset            | Vietnam Traffic Sign Dataset v3 |
+| License            | AGPL-3.0                        |
+
+The model returns traffic-sign codes such as `P-102`, `R-303`, and `W-224`. Vietnamese descriptions for these codes are provided separately in `label-mapping.json`.
+
+## Artifacts
+
+| File                    | Precision | Target platform                              |
+| ----------------------- | --------- | -------------------------------------------- |
+| `vtsr.pt`               | FP32      | PyTorch                                      |
+| `vtsr_int8.onnx`        | INT8      | ONNX Runtime, CPU, cross-platform deployment |
+| `vtsr_fp16.torchscript` | FP16      | TorchScript runtimes                         |
+| `vtsr_int8.engine`      | INT8      | NVIDIA TensorRT and Jetson devices           |
+| `label-mapping.json`    | —         | Traffic-sign code descriptions               |
+
+> The original FP32 PyTorch checkpoint is intentionally omitted. This repository provides optimized deployment artifacts only.
+
+## Usage
+
+Install dependencies:
+
+```bash
+pip install ultralytics
+```
+
+Run inference:
+
+```python
+from ultralytics import YOLO
+
+# Supported artifacts:
+# vtsr.pt
+# vtsr_int8.onnx
+# vtsr_fp16.torchscript
+# vtsr_int8.engine
+
+model = YOLO("vtsr_int8.onnx")
+
+results = model.predict(
+    source="traffic.jpg",
+    imgsz=640,
+    conf=0.25,
+)
+
+results[0].save("result.jpg")
+```
+
+See `label-mapping.json` for Vietnamese descriptions of traffic-sign codes.
+
+## Download from Hugging Face Hub
+
+```python
+from huggingface_hub import hf_hub_download
+
+repo_id = "liamxdev/vtsr"
+
+model_path = hf_hub_download(
+    repo_id=repo_id,
+    filename="vtsr_int8.onnx",
+)
+
+mapping_path = hf_hub_download(
+    repo_id=repo_id,
+    filename="label-mapping.json",
+)
+```
+
+Other artifacts can be downloaded in the same way:
+
+* `vtsr.pt`
+* `vtsr_fp16.torchscript`
+* `vtsr_int8.engine`
+
+## Benchmark
+
+See [benchmark.md](benchmark.md) for latency and throughput measurements.
+
+## Supported classes
+
+The model covers 56 Vietnamese traffic-sign codes in four broad groups:
+
+* `P-*`: prohibition signs.
+* `R-*`: mandatory and instruction signs.
+* `W-*`: warning signs.
+* `S-*` and `DP-*`: supplementary or special signs represented in the training dataset.
+
+See `label-mapping.json` for the complete list and Vietnamese meanings.
+
+## Training data
+
+The model was trained using version 3 of the [Vietnam Traffic Sign Dataset](https://universe.roboflow.com/giang-yp9g1/vietnam-traffic-sign-altsi/dataset/3) published on Roboflow Universe. The dataset metadata declares a CC BY 4.0 license.
+
+## Intended use
+
+* Educational and research projects.
+* Traffic-scene analysis prototypes.
+* Vietnamese traffic-sign detection demos.
+* CPU-oriented deployment through ONNX Runtime.
+* NVIDIA GPU and Jetson deployment through TensorRT.
+* Lightweight deployment through TorchScript.
+
+## Limitations
+
+* The model recognizes only the 56 classes listed in `label-mapping.json`.
+* Detection quality can decrease with small, blurred, occluded, damaged, poorly lit, or unusually angled signs.
+* Images outside the training distribution may produce missed detections or false positives.
+* A detection is not a substitute for official road-sign interpretation or safety-critical driving decisions.
+* Quantized and reduced-precision models may exhibit accuracy differences relative to the original PyTorch checkpoint.
+* TensorRT engines are hardware-specific and may need to be regenerated for different GPU architectures.
+
+## License
+
+The exported model contains Ultralytics YOLO components and is distributed under the AGPL-3.0 license. Dataset attribution and its CC BY 4.0 terms apply separately.
+
+For commercial licensing of Ultralytics components, see https://www.ultralytics.com/license.
+
+## Citation
+
+```bibtex
+@misc{vietnam_traffic_sign_altsi_dataset,
+  title        = {Vietnam Traffic Sign Dataset},
+  author       = {giang},
+  year         = {2024},
+  publisher    = {Roboflow Universe},
+  howpublished = {\url{https://universe.roboflow.com/giang-yp9g1/vietnam-traffic-sign-altsi}}
+}
+```

benchmark.md

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+## Environment
+
+- Platform: Google Colab
+- GPU: NVIDIA Tesla T4
+- Input size: 640×640
+- Batch size: 1
+- Warm-up runs: 30
+- Measured runs: 200
+
+## Results
+
+| Artifact | Mean Latency (ms) | Median Latency (ms) | P95 Latency (ms) | FPS (Median) |
+|------------|------------------:|--------------------:|-----------------:|--------------:|
+| ONNX INT8 | 733.704 | 634.253 | 1196.094 | 1.58 |
+| TorchScript FP16 | 15.526 | 15.174 | 17.666 | 65.90 |
+| TensorRT INT8 | 12.956 | 12.774 | 14.836 | 78.28 |
+
+TensorRT INT8 achieved the best latency and throughput on an NVIDIA Tesla T4 GPU. TorchScript FP16 delivered comparable performance, while the ONNX INT8 artifact showed substantially higher latency in this environment.

label-mapping.json

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+{
+  "DP-135": "Hết tất cả các lệnh cấm",
+  "P-102": "Cấm đi ngược chiều",
+  "P-103a": "Cấm xe ô tô",
+  "P-103b": "Cấm xe ô tô rẽ phải",
+  "P-103c": "Cấm xe ô tô rẽ trái",
+  "P-104": "Cấm xe máy",
+  "P-106a": "Cấm xe ô tô tải",
+  "P-106b": "Cấm xe ô tô tải có khối lượng chuyên chở lớn hơn quy định",
+  "P-107a": "Cấm xe ô tô khách",
+  "P-112": "Cấm người đi bộ",
+  "P-115": "Hạn chế tải trọng toàn bộ xe",
+  "P-117": "Hạn chế chiều cao",
+  "P-123a": "Cấm rẽ trái",
+  "P-123b": "Cấm rẽ phải",
+  "P-124a": "Cấm quay đầu xe",
+  "P-124b": "Cấm ô tô quay đầu xe",
+  "P-124c": "Cấm rẽ trái và quay đầu xe",
+  "P-127": "Tốc độ tối đa cho phép",
+  "P-128": "Cấm bóp còi",
+  "P-130": "Cấm dừng xe và đỗ xe",
+  "P-131a": "Cấm đỗ xe",
+  "P-137": "Cấm rẽ trái, rẽ phải",
+  "P-245a": "Đi chậm (Biển cấm cũ, hiện tại dùng W-245a)",
+  "R-301c": "Các xe chỉ được rẽ trái",
+  "R-301d": "Các xe chỉ được rẽ phải",
+  "R-301e": "Các xe chỉ được rẽ trái và đi thẳng",
+  "R-302a": "Hướng phải đi vòng chướng ngại vật sang phải",
+  "R-302b": "Hướng phải đi vòng chướng ngại vật sang trái",
+  "R-303": "Nơi giao nhau chạy theo vòng xuyến",
+  "R-407a": "Đường một chiều",
+  "R-409": "Chỗ quay xe",
+  "R-425": "Bệnh viện",
+  "R-434": "Bến xe buýt",
+  "S-509a": "Chiều cao an toàn (Biển phụ thuyết minh)",
+  "W-201a": "Chỗ ngoặt nguy hiểm vòng bên trái",
+  "W-201b": "Chỗ ngoặt nguy hiểm vòng bên phải",
+  "W-202a": "Nhiều chỗ ngoặt nguy hiểm liên tiếp vòng bên trái",
+  "W-202b": "Nhiều chỗ ngoặt nguy hiểm liên tiếp vòng bên phải",
+  "W-203b": "Đường bị thu hẹp về phía trái",
+  "W-203c": "Đường bị thu hẹp về phía phải",
+  "W-205a": "Đường giao nhau cùng cấp phía bên trái",
+  "W-205b": "Đường giao nhau cùng cấp phía bên phải",
+  "W-205d": "Đường giao nhau cùng cấp có dải trung tâm",
+  "W-207a": "Giao nhau với đường không ưu tiên (phía trước)",
+  "W-207b": "Giao nhau với đường không ưu tiên (phía bên phải)",
+  "W-207c": "Giao nhau với đường không ưu tiên (phía bên trái)",
+  "W-208": "Giao nhau với đường ưu tiên",
+  "W-209": "Giao nhau có tín hiệu đèn",
+  "W-210": "Giao nhau với đường sắt có rào chắn",
+  "W-219": "Dốc xuống nguy hiểm",
+  "W-224": "Đường người đi bộ cắt ngang",
+  "W-225": "Trẻ em",
+  "W-227": "Công trường",
+  "W-233": "Nguy hiểm khác",
+  "W-235": "Đường đôi",
+  "W-245a": "Đi chậm"
+}

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