Image Classification
Keras
computer-vision
defect-detection
resnet50
steel-manufacturing
transfer-learning
Instructions to use shashikantkaushik/Surface-defects-classification-of-the-hot-rolled-steel-strip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use shashikantkaushik/Surface-defects-classification-of-the-hot-rolled-steel-strip with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://shashikantkaushik/Surface-defects-classification-of-the-hot-rolled-steel-strip") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- cfb969cae7f950c6f05bd29f1635de18d1606d4a0b1c9b117276d396c38f2e95
- Size of remote file:
- 450 kB
- SHA256:
- 8b650fc385560e269eacc9683d43da2e7ac6f91b9f0ed845e1e29abc94a5128e
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