Image Classification
Transformers
PyTorch
English
emotion-detection
facial-expressio
deep-learning
cnn
Instructions to use ravi86/mood_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ravi86/mood_detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ravi86/mood_detector") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ravi86/mood_detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_resize": true, | |
| "size": { | |
| "shortest_edge": 256 | |
| }, | |
| "do_center_crop": true, | |
| "crop_size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "do_normalize": true, | |
| "image_mean": [0.5, 0.5, 0.5], | |
| "image_std": [0.5, 0.5, 0.5], | |
| "resample": 2, | |
| "feature_extractor_type": "ImageProcessor" | |
| } | |