YOLO11 Tripy

This example implements a YOLO11 classifier model using Tripy.

Running The Example

Run the following commands from the yolo11_tripy directory:

Install Dependencies:

bash

python3 -m pip install -r requirements.txt

Download ImageNet classes file:

bash

wget https://raw.githubusercontent.com/joannzhang00/ImageNet-dataset-classes-labels/main/imagenet_classes.txt

[Optional] Download some images:

bash

wget https://raw.githubusercontent.com/EliSchwartz/imagenet-sample-images/master/n01558993_robin.JPEG
wget https://raw.githubusercontent.com/EliSchwartz/imagenet-sample-images/master/n04389033_tank.JPEG

You can skip this step if you already have images you'd like to classify.

Build the model:
bash
```
python3 compile_classifier.py
```
You can configure various aspects of the model when you compile. Run python3 compile_classifier.py -h for details.
Run inference:
bash
```
python3 classify.py n01558993_robin.JPEG n04389033_tank.JPEG
```
The classify.py script allows you to pass one or more image file paths on the command line. The images are batched and classified in a single forward pass.