Zero-Shot Object Detection
KerasFormers
Keras
PyTorch
JAX
TensorFlow
owlvit
open-vocabulary
object-detection
Instructions to use zeromodels/owlvit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use zeromodels/owlvit-base-patch32 with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use zeromodels/owlvit-base-patch32 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/owlvit-base-patch32") - Notebooks
- Google Colab
- Kaggle
Upload kf_preprocessor.json with huggingface_hub
Browse files- kf_preprocessor.json +27 -0
kf_preprocessor.json
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{
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"library_name": "kerasformers",
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"kerasformers_version": "1.1.3",
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"preprocessor_module": "kerasformers.models.owlvit",
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"preprocessor_class": "OwlViTImageProcessor",
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"variant": "owlvit-base-patch32",
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"size": {
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"height": 768,
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"width": 768
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},
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"resample": "bicubic",
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"do_rescale": true,
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"rescale_factor": 0.00392156862745098,
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"do_normalize": true,
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"return_tensor": true,
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"data_format": null
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}
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