Instructions to use SyedHarshath/traffic-analytics-yolo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use SyedHarshath/traffic-analytics-yolo with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("SyedHarshath/traffic-analytics-yolo") - Notebooks
- Google Colab
- Kaggle
Download pascal_classes.txt from SyedHarshath/traffic-analytics-yolo: direct link, hf CLI and curl.
- Browser
- Download file 135 Bytes
-
https://huggingface.co/SyedHarshath/traffic-analytics-yolo/resolve/main/pascal_classes.txt
- Command line
-
hf download hf://SyedHarshath/traffic-analytics-yolo/pascal_classes.txt
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curl -L -o pascal_classes.txt https://huggingface.co/SyedHarshath/traffic-analytics-yolo/resolve/main/pascal_classes.txt
135 Bytes
| aeroplane | |
| bicycle | |
| bird | |
| boat | |
| bottle | |
| bus | |
| car | |
| cat | |
| chair | |
| cow | |
| diningtable | |
| dog | |
| horse | |
| motorbike | |
| person | |
| pottedplant | |
| sheep | |
| sofa | |
| train | |
| tvmonitor | |