Instructions to use mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50") model = AutoModelForObjectDetection.from_pretrained("mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01d78278269a517118fbdc644680d792e80e136b982753146833be56a96ec6ca
- Size of remote file:
- 174 MB
- SHA256:
- 6f6e2ae0b27fa6f40a11c6a6a093ed0558bf40164d898eaceb400dec5cfa0fd8
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