Update README.md

README.md

@@ -2,22 +2,24 @@
 license: mit
 ---
 
-explain a high-level overview of your code and how to run your code: 
-including what packages I must install, and 
-where the data came from and in which folder it must go.
-
-
 # Face Recognition Model
+"CSSE416-final-project/faceRecogModel" is the Hugging Face (HF) repository we deployed the final, fully trained model to. Checkout the HF Space "CSSE416-final-project/faceRecogModel" to easily test and play around with the model.
 
 
 ## Files
 - modelWeights101.bin
-  - Weights of model we trained using the Gebru server
+  - Weights of model we created by training on Gebru servers
 - app.py, model.py, and config.json
-  - Standard files used by Hugging Face (HF) to setup the architecture of the model in conjunction with the weights
+  - Standard files used by Hugging Face to setup the architecture of the model in conjunction with the weights
 - updateHFtemplate
   - Used this file to update the above files in the Hugging Face repository
-  - The weights file did not update properly using standard gate, so we used Hugging Face Hub with this file to properly update the repo
+  - The weights file did not update properly using standard Git, so we used Hugging Face Hub with this file to properly update the repo
+  - Could also use Git LFS instead
+- testModelWeights.ipynb, testData
+  - Converts the weights file into the model
+  - Test the model on a folder of images with names of the subfolders representing classes
+    - We created an easy to use collection of images called "testData"
+    
 
 ## Neccessary Package
   - Since the model all runs on Hugging Face, you don't need to install any packages.
@@ -31,5 +33,6 @@ where the data came from and in which folder it must go.
 ## Running
   - You can run this model using the Hugging Face Space: CSSE416-final-project/faceRecogModel
     - You can upload images through the Space UI.
-  - Alternatively, if you want to run the model locally, you can use <<this>> file to load the weights.
+  - Alternatively, if you want to test the model locally, you can use "testModelWeights.ipynb"
+    - You might be able to run the notebook on CoLab as well