Create README.md

Author: BradleyHWQ

README.md

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+# Autoencoder-Image-Compression
+Pytorch implementation for image compression and reconstruction via autoencoder
+
+This is an autoencoder with cylic loss and coding parsing loss for image compression and reconstruction. Network backbone is simple 3-layer 
+fully conv (encoder) and symmetrical for decoder. Finally it can achieve 21 mean PSNR on CLIC dataset (CVPR 2019 workshop).
+
+You can download
+training data from this url: https://drive.google.com/drive/folders/1wU1CO6WcQOraIaY2KSk7cRVaAXcm_A2R?usp=sharing
+validation data: https://drive.google.com/drive/folders/113EcrAdcxfVqs8BVt4PZjwUEyVz7VVa-?usp=sharing
+
+Organize your data with this structure:
+
+Data
+  |
+  |---train
+        |
+        |---image1.xxx
+        |---image2.xxx
+        .
+        .
+        .
+
+Data_valid
+  |
+  |---train
+        |
+        |---image1.xxx
+        |---image2.xxx
+        .
+        .
+        .
+
+You can train your own model via run_train.sh and modify config as your needs. Prediction for the valid data via run_test.sh