Update README.md

README.md

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 # Malaria-Detector-Streamlit
 A Neural Network to Detect Malaria Parasites in Blood Samples
+
+## Background
+*Plasmodium falciparum* is a common type of malaria found across Africa. It is also the most deadly form of malaria. You can detect *P. falciparum* by taking blood samples and inspecting them under a microscope. Infected red blood cells may have a darker patch which is the parasite. To train this model, I used a dataset made in Uganda by [J. Quinn et al.](http://air.ug/microscopy/)
+
+## Steps
+1. Download the dataset from the link above.
+2. Simply use the tensorflow object detection API to train a model
+3. Export the inference graph and call it frozen_inference_graph.pb
+4. Move the website.py and correct.py files into the object_detection directory
+5. On line 76 of correct.py change the MODEL_NAME to the name of your exported model
+6. Move both of the images into the object_detection directory