Instructions to use aadd77551/AI-image-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use aadd77551/AI-image-detector with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://aadd77551/AI-image-detector") - Notebooks
- Google Colab
- Kaggle
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pipeline_tag: image-classification
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tags:
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tags:
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- image-classification
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- tensorflow
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- keras
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pipeline_tag: image-classification
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---
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# Your Model Name
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這是使用 TensorFlow 和 Keras 訓練的圖像分類模型。模型是基於 [某某數據集](https://example.com) 訓練的。
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## 使用方法
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### Python 示例
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```python
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import tensorflow as tf
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import numpy as np
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# 加載模型
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model = tf.keras.models.load_model("path/to/your/saved_model")
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# 使用模型進行預測
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image = tf.keras.preprocessing.image.load_img("path/to/your/image.jpg", target_size=(224, 224))
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input_arr = tf.keras.preprocessing.image.img_to_array(image)
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input_arr = np.array([input_arr]) # 將單張圖片轉換為批處理格式
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predictions = model.predict(input_arr)
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print(predictions)
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