Insiyah Hajoori and Ryan Birmingham

Using a machine learning toolkit of your choice, create a tool which identifies objects in the image, then returns positions in pixels corresponding to bounding boxes of a user-selected class of object in the image. For example, given an image with both cats and dogs, return bounding boxes for only cats.

• Python 3.7.3 or above
• Node v12.16.1 or above
• You will need the weights. Get them from: https://drive.google.com/drive/folders/1lNKCbOM7VSRLIvHB2jh7XQAThPRHmpt_?usp=sharing

1. Clone this repository.
2. Download the weights from the link above.
3. Put the downloaded weights into the following folder:

 gsoc_model

4. Your gsoc_model folder will now have the following contents:

 coco.names 
 gsoc.cfg
 gsoc.weights
 gsoc.txt
 

5. On the terminal:

 cd caMicroscope
 pip install virtualenv
 source env/Scripts/activate
 pip install -r requirements.txt

6. Install Pyrebase4 4.3.0

pip install Pyrebase4

7. Run the Flask app

python app.py

8. Choose a file from Images
9. Your File has been detected. Thanks!

Hrishabh Digaari - LinkedIn

• https://arxiv.org/pdf/1506.02640.pdf
• https://arxiv.org/pdf/1804.02767.pdf
• https://flask.palletsprojects.com/
• https://firebase.google.com/docs/web/setup