Muhammad Firdho
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Update README.md
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README.md
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# 🎯
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This is an image classification model trained to classify medical waste into 4 categories, namely cytotoxic, infectious, pathological, and pharmaceutical. The model is based on the Inception v3 architecture and has been adapted to a specific dataset for the task of medical waste classification.
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# 🎯 Model Description
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The model is based on the Inception v3 architecture with modifications to the fully connected layers for adapting it to the specific image classification task. The architecture consists of a feature extractor followed by a global average pooling layer and fully connected layers with ReLU activation and dropout.
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# 🎯 Usage
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You can use the model that I have saved in pt format as follows:
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plt.show()
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```
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# 🎯 Image Classification Model for Medical Waste Classification
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This is an image classification model trained to classify medical waste into 4 categories, namely cytotoxic, infectious, pathological, and pharmaceutical. The model is based on the Inception v3 architecture and has been adapted to a specific dataset for the task of medical waste classification.
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# 🎯 Model Description
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The model is based on the Inception v3 architecture with modifications to the fully connected layers for adapting it to the specific image classification task. The architecture consists of a feature extractor followed by a global average pooling layer and fully connected layers with ReLU activation and dropout.
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# 🎯 Dataset Used
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The train data for each category is 175 images and the validation data is 50 images.
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The dataset used comes from collecting it myself.
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# 🎯 Final training results
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The model gets the following results from training
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- Train Loss: 0.243
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- Val. Losses: 0.252
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- Train Acc: 93.73%
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- Val. Acc: 93.92%
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# 🎯 Usage
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You can use the model that I have saved in pt format as follows:
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plt.show()
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```
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The following are the output results from using this coding
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