README.md

---
license: apache-2.0
---

# Shot Type

This model predicts an image's cinematic shot type [clean single, double, group, over the shoulder, insert, establishing].  The model is a DinoV2 with registers backbone (initiated with `facebook/dinov2-with-registers-large` weights) and trained on a diverse set of five thousand human-annotated images.

## How to use:
```python

import torch
from PIL import Image
from transformers import AutoImageProcessor
from transformers import AutoModelForImageClassification

image_processor = AutoImageProcessor.from_pretrained("facebook/dinov2-with-registers-large")
model = AutoModelForImageClassification.from_pretrained('aslakey/depth_of_field')
model.eval()

# Model labels: [clean_single, double, group, over_the_shoulder, insert, establishing]
image = Image.open('cinematic_shot.jpg')
inputs = image_processor(image, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs)

predicted_label = outputs.logits.argmax(-1).item()
print(model.config.id2label[predicted_label])
```

## Performance:


| Category | Precision | Recall |
|----------|-----------|--------|
| clean_single      | 81%        | 89%     |
| double        | 80%       | 72%    |
| group        | 91%       | 74%    |
| over the shoulder        | 60%       | 67%    |
| establishing        | 91%       | 77%    |