Object Detection
Transformers
PyTorch
TensorBoard
detr
Generated from Trainer
computer-vision
its
autonomous-driving
Instructions to use mcity-data-engine/fisheye8k_facebook_detr-resnet-101-dc5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcity-data-engine/fisheye8k_facebook_detr-resnet-101-dc5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="mcity-data-engine/fisheye8k_facebook_detr-resnet-101-dc5")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("mcity-data-engine/fisheye8k_facebook_detr-resnet-101-dc5") model = AutoModelForObjectDetection.from_pretrained("mcity-data-engine/fisheye8k_facebook_detr-resnet-101-dc5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d1131815c2b1e762b08ab30fac91d6bb759d7b506c0fb2ddf86a703d29483ef
- Size of remote file:
- 5.56 kB
- SHA256:
- bd0e1d88f9f31fb57a26e1959a1e54470722985eea48280ec968ca6c00cf31e0
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