Multiobject Detection using Fastai

How to build a multiobject detection model using fastai?
I want to build a model that creates bbox around the objects that I want to detect and is able to properly identify them.

Hello,
Building a multi-object detection model using fastai involves several steps. Here’s a high-level overview to get you started: Official Login Link

  1. Set Up Your Environment
    Ensure you have the necessary libraries installed:

Python

!pip install fastai
2. Prepare Your Data
You need a dataset with images and corresponding bounding box annotations. A common format is COCO or Pascal VOC. For example, you can use the Pascal VOC dataset:

Python

from fastai.vision.all import *
path = untar_data(URLs.PASCAL_2007)3. Load and Annotate Data
Use fastai’s get_annotations function to load your images and their bounding boxes:

Python

imgs, lbl_bbox = get_annotations(path/‘train.json’)
img2bbox = dict(zip(imgs, lbl_bbox))
Best Regards
esther598

Well, could you tell me the part on how to train the model on the data.

Thanks for your response :slight_smile:

I’ve been following this Tutorial and noticed that it concludes with a caveat: " show_results and predict both do not currently work. I’d recommend utilizing the IceVision library for your Object Detection needs."

However, upon exploring IceVision, I found the documentation to be lacking and the codebase hasn’t been updated in two years, which makes me hesitant to adopt it for my needs.