Readme

README.md

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-# keras-cam
+## Keras implementation of class activation mapping
+
+Original paper project page: http://cnnlocalization.csail.mit.edu
+Code with Caffe / matcaffe interface: https://github.com/metalbubble/CAM
+
+Blog post about this project: http://jacobcv.blogspot.com/2016/08/class-activation-maps-in-keras.html 
+
+
+![enter image description here](https://raw.githubusercontent.com/jacobgil/keras-cam/master/examples/mona_lisa.jpg)
+
+
+This project implements class activation maps with Keras.
+Class activation maps are a simple technique to get the image regions relevant to a certain class.
+
+This was fined tuned on VGG16 with images from here: http://pascal.inrialpes.fr/data/human
+The model in model.py is a two category classifier, used to classify person / not a person.
+
+    usage: cam.py [-h] [--train TRAIN] [--image_path IMAGE_PATH]
+              [--output_path OUTPUT_PATH] [--model_path MODEL_PATH]
+              [--dataset_path DATASET_PATH]
+
+	optional arguments:
+	  -h, --help            show this help message and exit
+	  --train TRAIN         Train the network or visualize a CAM
+	  --image_path IMAGE_PATH
+	                        Path of an image to run the network on
+	  --output_path OUTPUT_PATH
+	                        Path of an image to run the network on
+	  --model_path MODEL_PATH
+	                        Path of the trained model
+	  --dataset_path DATASET_PATH
+	                        Path to image dataset. Should have pos/neg folders,
+	                        like in the inria person dataset.
+	                        http://pascal.inrialpes.fr/data/human/
+