/Computer-Vision-Flower-Classificatiion-with-ResNet50

Computer Vision Flower Classificatiion with ResNet50, TensorFlow and Streamlit

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Computer Vision Flower Classification with Resnet50

Computer Vision Flower Classification with Resnet50, TensorFlow and Streamlit

The Flower Classification Model was trained using the ResNet50 Architecture and the Transfer Learning Deep Learning Technique, also with the Google Colab GPU and with over 8000 Flower Images. The U.I. was built with Streamlit. It can be test it with uploading a Picture.

Run it Locally

Test it Locally by running the app.py file, built with Streamlit Remember first to train the model in the flower_classification.ipynb file and saved in the the model folder.

App made with Streamlit

streamlit run app.py

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