@huggingface/tasks/src/tasks/zero-shot-object-detection/about.md

List of ML tasks for huggingface.co/tasks

## Use Cases

Zero-shot object detection models can be used in any object detection application where the detection involves text queries for objects of interest.

### Object Search

Zero-shot object detection models can be used in image search. Smartphones, for example, use zero-shot object detection models to detect entities (such as specific places or objects) and allow the user to search for the entity on the internet.

### Object Counting

Zero-shot object detection models are used to count instances of objects in a given image. This can include counting the objects in warehouses or stores or the number of visitors in a store. They are also used to manage crowds at events to prevent disasters.

### Object Tracking

Zero-shot object detectors can track objects in videos.

## Inference

You can infer with zero-shot object detection models through the `zero-shot-object-detection` pipeline. When calling the pipeline, you just need to specify a path or HTTP link to an image and the candidate labels.

```python
from transformers import pipeline
from PIL import Image

image = Image.open("my-image.png").convert("RGB")

detector = pipeline(model="google/owlvit-base-patch32", task="zero-shot-object-detection")

predictions = detector(
    image,
    candidate_labels=["a photo of a cat", "a photo of a dog"],
)

# [{'score': 0.95,
#   'label': 'a photo of a cat',
#   'box': {'xmin': 180, 'ymin': 71, 'xmax': 271, 'ymax': 178}},
#   ...
# ]
```

# Useful Resources

- [Zero-shot object detection task guide](https://huggingface.co/docs/transformers/tasks/zero_shot_object_detection)

This page was made possible thanks to the efforts of [Victor Guichard](https://huggingface.co/VictorGuichard)