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+# PathologyGo
+Core components of PathologyGo, the AI assistance system designed for histopathological inference.
+
+<b>Dependency</b>
+
+* Docker
+* Python 2.7 and 3.x
+* openslide
+* tensorflow_serving
+* grpc
+* pillow
+* numpy
+* opencv-python
+
+<b>Dockerized TensorFlow Serving</b>
+
+* GPU version: [GitHub](https://github.com/physicso/tensorflow_serving_gpu), [Docker Hub](https://hub.docker.com/r/physicso/tf_serving_gpu).
+* CPU version: [Docker Hub](https://hub.docker.com/r/tensorflow/serving).
+
+<b>Quick Start</b>
+
+This code is easy to implement. Just change the path to your data repo:
+
+```python
+from utils import config
+GPU_LIST = config.INFERENCE_GPUS
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = ','.join('{0}'.format(n) for n in GPU_LIST)
+from inference import Inference
+
+
+if __name__ == '__main__':
+    pg = Inference(data_dir='/path/to/data/', data_list='/path/to/list',
+                    class_num=2, result_dir='./result', use_level=1)
+    pg.run()
+
+```
+
+You may configure all the model-specific parameters in `utils/config.py`.
+
+<b>Example</b>
+
+Use the [CAMELYON16](https://camelyon16.grand-challenge.org/) test dataset as an example, 
+the data path should be `/data/CAMELYON/`, and the content of the data list is
+
+```
+001.tif
+002.tif
+...
+```
+
+The predicted heatmaps will be written to `./result`.
+
+<b>DIY Notes</b>
+
+You may use other exported models. You can change the model name for TensorFlow Serving in `utils/config.py`. Just remember to modify `class_num` and `use_level`.
+
+Note that the default input / output tensor name should be `input` / `output`.