Update README.md

README.md

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-license: mit
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+---
+license: mit
+metrics:
+- accuracy 99.51%
+tags:
+- OrientationDetection
+- TextOrientation
+---
+
+Updated CNN .keras model with input layer 256*256 RGB, and 1 output node ranging from 0 (no rotation) to 1 (180 degrees). 
+
+Its accuracy on the dataset in the link below is 99.51%, and the AUC (Area Under Curve) metric is 0.9990. 
+https://drive.google.com/file/d/1WENDw-Ggwy32KIdMlMmuF6NcO0gH3mC8/view?usp=sharing
+
+It only recognizes 0 vs 180 degrees as there's another robust way to distinguish +- 90 from 0 and 180 degrees (another model under UTSC DSU). 
+Additionally, the dataset only contains upright images because the training program generates the 180-degrees counterparts on the fly. 
+As you will see, the model is only trained on text slices resulted from my proprietary preprocessing methods 
+(old version already on GitHub https://github.com/digitalutsc/ml_image_tool, but I will update it soon), 
+So directly feeding the page images to the model may not work well. 
+
+I used MobileNetV2 with imagenet weights as the backbone, and the accuracy proves the method to be very successful.
+
+![hist_outputs](https://cdn-uploads.huggingface.co/production/uploads/67fc828a84224b6e5a42d981/uQWaG8Nsq5Xx6IcatFzEm.png)