Object Detection
Transformers
PyTorch
TensorBoard
deta
Generated from Trainer
swin
traffic
automotive
ITS
computer-vision
Instructions to use mcity-data-engine/fisheye8k_jozhang97_deta-swin-large-o365 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcity-data-engine/fisheye8k_jozhang97_deta-swin-large-o365 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="mcity-data-engine/fisheye8k_jozhang97_deta-swin-large-o365")# Load model directly from transformers import AutoModelForObjectDetection model = AutoModelForObjectDetection.from_pretrained("mcity-data-engine/fisheye8k_jozhang97_deta-swin-large-o365", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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tags:
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- generated_from_trainer
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datasets:
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model-index:
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- name: fisheye8k_jozhang97_deta-swin-large-o365
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results: []
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- Transformers 4.48.3
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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tags:
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- generated_from_trainer
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datasets:
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- Voxel51/fisheye8k
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model-index:
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- name: fisheye8k_jozhang97_deta-swin-large-o365
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results: []
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- Transformers 4.48.3
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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