Update pages/1_Maximally_activating_patches.py

pages/1_Maximally_activating_patches.py

@@ -13,6 +13,15 @@ from backend.utils import load_dataset_dict
 HIGHTLIGHT_COLOR = '#e7bcc5'
 st.set_page_config(layout='wide')
 
+
+st.title('Maximally activating image patches')
+st.write('> What patterns maximally activate this channel in ConvNeXt model?')
+st.write("""The maximally activating image patches method is a technique used in visualizing the interpretation of convolutional neural networks. 
+It works by identifying the regions of the input image that activate a particular neuron in the convolutional layer, 
+thus revealing the features that the neuron is detecting. To achieve this, the method generates image patches then feeds into the model while monitoring the neuron's activation. 
+The algorithm then selects the patch that produces the highest activation and overlays it on the original image to visualize the features that the neuron is responding to.
+""")
+
 # -------------------------- LOAD DATASET ---------------------------------
 dataset_dict = load_dataset_dict()