Update README.md

README.md

@@ -6,3 +6,96 @@ license: mit
 
 This repository contains code to optimize PyTorch image models using ONNX Runtime and TensorRT, achieving up to 8x faster inference speeds. Read the full blog post [here](https://dicksonneoh.com/portfolio/supercharge_your_pytorch_image_models/).
 
+## Installation
+Create and activate a conda environment:
+
+```bash
+conda create -n supercharge_timm_tensorrt python=3.11
+conda activate supercharge_timm_tensorrt
+```
+ Install required packages:
+
+
+```bash
+pip install timm
+pip install onnx
+pip install onnxruntime-gpu==1.19.2
+pip install cupy-cuda12x
+pip install tensorrt==10.1.0 tensorrt-cu12==10.1.0 tensorrt-cu12-bindings==10.1.0 tensorrt-cu12-libs==10.1.0
+```
+
+Install CUDA dependencies:
+```bash
+conda install -c nvidia cuda=12.2.2 cuda-tools=12.2.2 cuda-toolkit=12.2.2 cuda-version=12.2 cuda-command-line-tools=12.2.2 cuda-compiler=12.2.2 cuda-runtime=12.2.2
+```
+
+Install cuDNN:
+```bash
+conda install cudnn==9.2.1.18
+```
+
+Set up library paths:
+```bash
+export LD_LIBRARY_PATH="/home/dnth/mambaforge-pypy3/envs/supercharge_timm_tensorrt/lib:$LD_LIBRARY_PATH"
+export LD_LIBRARY_PATH="/home/dnth/mambaforge-pypy3/envs/supercharge_timm_tensorrt/lib/python3.11/site-packages/tensorrt_libs:$LD_LIBRARY_PATH"
+```
+
+## Running the code
+
+The following codes correspond to the steps in the blog post.
+
+### PyTorch latency benchmark:
+   ```bash
+   python 01_pytorch_latency_benchmark.py
+   ```
+Read more [here](https://dicksonneoh.com/portfolio/supercharge_your_pytorch_image_models//#-baseline-latency)
+
+### Convert model to ONNX:
+   ```bash
+   python 02_convert_to_onnx.py
+   ```
+Read more [here](https://dicksonneoh.com/portfolio/supercharge_your_pytorch_image_models//#-convert-to-onnx)
+
+### ONNX Runtime CPU inference:
+   ```bash
+   python 03_onnx_cpu_inference.py
+   ```
+Read more [here](https://dicksonneoh.com/portfolio/supercharge_your_pytorch_image_models//#-onnx-runtime-on-cpu)
+
+### ONNX Runtime CUDA inference:
+   ```bash
+   python 04_onnx_cuda_inference.py
+   ```
+Read more [here](https://dicksonneoh.com/portfolio/supercharge_your_pytorch_image_models//#-onnx-runtime-on-cuda)
+
+### ONNX Runtime TensorRT inference:
+   ```bash
+   python 05_onnx_trt_inference.py
+   ```
+Read more [here](https://dicksonneoh.com/portfolio/supercharge_your_pytorch_image_models//#-onnx-runtime-on-tensorrt)
+
+### Export preprocessing to ONNX:
+   ```bash
+   python 06_export_preprocessing_onnx.py
+   ```
+Read more [here](https://dicksonneoh.com/portfolio/supercharge_your_pytorch_image_models//#-bake-pre-processing-into-onnx)
+
+### Merge preprocessing and model ONNX:
+   ```bash
+   python 07_onnx_compose_merge.py
+   ```
+Read more [here](https://dicksonneoh.com/portfolio/supercharge_your_pytorch_image_models//#-bake-pre-processing-into-onnx)
+
+### Run inference on merged model:
+   ```bash
+   python 08_inference_merged_model.py
+   ```
+Read more [here](https://dicksonneoh.com/portfolio/supercharge_your_pytorch_image_models//#-bake-pre-processing-into-onnx)
+
+### Run inference on video:
+   ```bash
+   python 09_video_inference.py sample.mp4 output.mp4 --live 
+   ```
+
+<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/6195f404c07573b03c61702c/lOmu7KaqrihRDVcQVJDi0.mp4"></video>
+