# DS Task Recycling Project

This project is a toy project for training and quality assurance purposes. It involves developing a simple Flask API that processes an image (or a hardcoded image) of a motherboard and detects memory modules present on it. The API will return the image with bounding boxes drawn around each detected memory module.

## Project Overview

- **Input Types:**

  - Image upload via the Flask API.
  - A hardcoded image for testing purposes.
- **Dataset:**

  - 20 pictures of motherboards with memory.
  - 20 pictures of motherboards without memory.
- **Output:**

  - An annotated image with bounding boxes around each detected memory module.
    For example, if there are two memory modules, two boxes are drawn; if only one is detected, then one box is drawn.
- **Annotation Tool Suggestion:**

  - We suggest using [makesense.ai](https://www.makesense.ai/) for manual annotation if needed.

## Task Details

The developer is required to research and answer the following questions as part of the task:

1. **Algorithm Choice:**

   - Which algorithm will you use for detecting the memory modules?
   - Why do you choose this particular algorithm?
2. **Hardware Considerations:**

   - Does CPU or GPU have an impact on your decision? Please explain.
3. **Video Input:**

   - What if a video is provided instead of single images?
   - Does your approach change when processing videos? Please describe your approach.

## Proposed Flask API Implementation

1. **API Endpoints:**

   - An endpoint for uploading images which processes and returns the annotated image.
   - An endpoint parameter for using a hardcoded image for testing purposes.
2. **Processing Workflow:**

   - Receive an image (either via file upload or from a hardcoded source).
   - Apply the chosen object detection algorithm to detect memory modules.
   - Draw bounding boxes around each detected memory module.
   - Return the annotated image to the user.

## Data Set:

Dataset in on the `training` folder. And there is `memory` and `no_memory` subfolder in it.