Update README.md

README.md

@@ -8,63 +8,38 @@ Classification of lego technic pieces under basic room lighting conditions
 ## Model Details
 
 ### Model Description
-CNN designed without using a pre-trained model to classify images of lego pieces into 7 categories. Achieved a 93% validation accuracy
+CNN designed from the ground up, without using a pre-trained model to classify images of lego pieces into 7 categories. <br>
+Achieved a 93% validation accuracy
 
 - **Developed by:** Aveek Goswami, Amos Koh
 - **Funded by [optional]:** Nullspace Robotics Singapore
 - **Model type:** Convolutional Neural Network
 
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
+### Model Sources
 
 - **Repository:** https://github.com/magichampz/lego-sorting-machine-ag-ak
-- **Demo [optional]:** 
 ![image/gif](https://cdn-uploads.huggingface.co/production/uploads/652dc3dab86e108d0fea458c/E7UZXLWPvU_39cxrF49jD.gif)
 
 ## Uses
+The tflite model (model.tflite) was loaded into a Raspberry Pi running a live object detection script. <br>
+The Pi could then detect lego technic pieces in real time as the pieces rolled on a conveyor belt towards the Pi Camera
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
+## Bias, Limitations and Recommendations
+The images of the lego pieces used to train the model were taken in 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
 [More Information Needed]
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
 
-Use the code below to get started with the model.
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
 
-[More Information Needed]
 
 ## Training Details
 
 ### Training Data
+- **Data:** https://huggingface.co/datasets/magichampz/lego-technic-pieces
 
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
 
@@ -147,17 +122,17 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ### Compute Infrastructure
 
-[More Information Needed]
+Trained on Google Collabs using the GPU available
 
 #### Hardware
 
-[More Information Needed]
-
-#### Software
+Model loaded into a raspberry pi 3 connected to a PiCamera v2 <br>
+RPi mounted on a holder and conveyor belt set-up built with lego
 
-[More Information Needed]
 
-## Citation [optional]
+## Citation
+Model implemented on the raspberry pi using the ideas from PyImageSearch's blog: <br>
+https://pyimagesearch.com/2017/09/18/real-time-object-detection-with-deep-learning-and-opencv/
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->