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--- |
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license: mit |
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datasets: |
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- microsoft/cats_vs_dogs |
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--- |
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# Report Issue |
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If you encounter any problems with downloading or using the model, please report the issue by creating one at the following GitHub repository: https://github.com/parneetsingh022/dog-cat-classification.git |
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# Demo |
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https://huggingface.co./spaces/parneetsingh022/cat-vs-dog |
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# Loading and using the model. |
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In order to download and use the model follow these steps: |
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1. Clone this reposetory: |
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``` |
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git clone https://github.com/parneetsingh022/dog-cat-classification.git |
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``` |
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2. Download transformers liberary |
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``` |
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pip install transformers |
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``` |
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3. |
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After installation, you can utilize the model in other scripts outside of this directory `custom_classifier` as described below: |
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Required Imports: |
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```python |
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import torch |
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from PIL import Image |
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from torchvision import transforms |
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from custom_classifier.configuration import CustomModelConfig |
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from custom_classifier.model import CustomClassifier |
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``` |
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Loading the model: |
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```python |
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model_name = "parneetsingh022/dog-cat-classification" |
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config = CustomModelConfig.from_pretrained(model_name) |
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model = CustomClassifier.from_pretrained(model_name, config=config) |
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``` |
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Pridicting probability of individual class: |
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```python |
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# Load an example image |
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image_path = "dog.jpeg" |
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outputs = model.predict(image_path) |
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print(outputs) |
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``` |
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Output: {'cat': 0.003, 'dog': 0.997} |
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Getting class name instead of probabilities: |
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```python |
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# Load an example image |
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image_path = "dog_new.jpeg" |
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outputs = model.predict(image_path, get_class=True) |
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print(output) |
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``` |
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Output: 'dog' |