Update README.md

README.md

@@ -1,3 +1,77 @@
----
-license: cc
----
+---
+license: cc
+---
+
+## Install following python libs
+
+```
+pip3 install tensorflow
+pip3 install tensorflowjs
+pip3 install tf2onnx
+pip3 install onnxruntime
+pip3 install pillow
+pip3 install optimum[exporters]
+```
+Change to compatible version of numpy for tensorflow
+```
+pip3 uninstall numpy
+pip3 install numpy==1.23.5
+```
+
+## Node Install 
+Download install project dependencies.
+```
+npm install
+```
+
+### Summary of Commands:
+
+- Run the Node training script to save the Layers Model.
+- Convert tfjs_layers_model → tfjs_graph_model
+- Convert graph model to onnx
+- Validate onnx structure
+- Test Model
+
+# 1. Create Tensorflow model in node
+
+This will loop through the training images taking base folder name as the label for the images to be associated against.
+Once complete saved-model/model.json is created.
+
+```
+node generate.js
+```
+
+# 2. Convert Model
+
+Convert from layers to graph model this is required to generate an onnx from tf2onnx
+
+```
+tensorflowjs_converter --input_format=tfjs_layers_model \  --output_format=tfjs_graph_model \  ./saved-model/layers-model/model.json \  ./saved-model/graph-model
+```
+
+# 3. Convert to ONNX Model
+
+This will convert to a ONNX model to be used with transformers.js on web or nodejs.
+```
+python3 -m tf2onnx.convert --tfjs ./saved-model/graph-model/model.json --output ./saved-model/model.onnx
+```
+
+Unable to figure a way to use Optimum with tensorflow.js models atm..
+
+# 4. Validate ONNX
+
+Make sure the conversion worked and no issues
+```
+python3 validate_onnx.py
+```
+
+# 5. Test ONNX Model python
+
+update the image path in the code to point to an image to confirm working as expected 
+- I tested against one of the trained image that should give 1.
+```
+python3 test_image.py
+```
+Inference outputs: [array([[0., 1.]], dtype=float32)]
+
+