Image Classification
TF-Keras
English
resnet
medical
bio
biology
Pneumonia_detection
X-Ray_Classfication
Instructions to use ryefoxlime/PneumoniaDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use ryefoxlime/PneumoniaDetection with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("ryefoxlime/PneumoniaDetection") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Push Keras model using huggingface_hub.
3801f04 -
Pneumonia Detection with an accuracy of 91%
Model Architecture: - model = Sequential() - model.add(base_model) - model.add(AveragePooling2D(pool_size=(2, 2), strides=2)) - model.add(Flatten()) - model.add(Dense(256, activation="relu")) - model.add(Dense(128, activation="relu")) - model.add(Dense(2, activation="softmax")) - model.compile( loss="sparse_categorical_crossentropy", optimizer=Adam(learning_rate=0.000035), metrics=["sparse_categorical_accuracy"], ) Confusion Matrix for the model  model evaluation result: c7308c1