Delete README.md

README.md

@@ -1,65 +0,0 @@
-# Overview
-This repository provides an ensemble model to combine a YoloV8 model exported from the [Ultralytics](https://github.com/ultralytics/ultralytics) repository with NMS post-processing. The NMS post-processing code contained in [models/postprocess/1/model.py](models/postprocess/1/model.py) is adapted from the [Ultralytics ONNX Example](https://github.com/ultralytics/ultralytics/blob/4b866c97180842b546fe117610869d3c8d69d8ae/examples/YOLOv8-OpenCV-ONNX-Python/main.py).
-
-
-For more information about Triton's Ensemble Models, see their documentation on [Architecture.md](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/architecture.md) and some of their [preprocessing examples](https://github.com/triton-inference-server/python_backend/tree/main/examples/preprocessing).
-
-# Directory Structure
-```
-models/
-    yolov8_onnx/
-        1/
-            model.onnx
-        config.pbtxt
-        
-    postprocess/
-        1/
-            model.py
-        config.pbtxt
-        
-    yolov8_ensemble/
-        1/
-            <Empty Directory>
-        config.pbtxt
-README.md
-main.py
-```
-
-
-# Quick Start
-1. Install [Ultralytics](https://github.com/ultralytics/ultralytics) and TritonClient
-```
-pip install ultralytics==8.0.51 tritonclient[all]==2.31.0
-```
-
-2. Export a model to ONNX format:
-```
-yolo export model=yolov8n.pt format=onnx dynamic=True opset=16
-```
-
-3. Rename the model file to `model.onnx` and place it under the `/models/yolov8_onnx/1` directory (see directory structure above).
-
-4. (Optional): Update the Score and NMS threshold in [models/postprocess/1/model.py](models/postprocess/1/model.py#L59)
-
-5. (Optional): Update the [models/yolov8_ensemble/config.pbtxt](models/yolov8_ensemble/config.pbtxt) file if your input resolution has changed.
-
-6. Build the Docker Container for Triton Inference:
-```
-DOCKER_NAME="yolov8-triton"
-docker build -t $DOCKER_NAME .
-```
-
-6. Run Triton Inference Server:
-```
-DOCKER_NAME="yolov8-triton"
-docker run --gpus all \
-    -it --rm \
-    --net=host \
-    -v ./models:/models \
-    $DOCKER_NAME
-```
-
-7. Run the script with `python main.py`. The overlay image will be written to `output.jpg`.
-
-
-