https://github.com/clementsan/object_detection_gradio
Object detection with Gradio user interface
https://github.com/clementsan/object_detection_gradio
ai computer-vision deep-learning gradio object-detection
Last synced: 6 months ago
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Object detection with Gradio user interface
- Host: GitHub
- URL: https://github.com/clementsan/object_detection_gradio
- Owner: clementsan
- Created: 2024-11-19T19:46:42.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-01-06T23:00:15.000Z (9 months ago)
- Last Synced: 2025-02-04T13:03:31.661Z (8 months ago)
- Topics: ai, computer-vision, deep-learning, gradio, object-detection
- Language: Python
- Homepage:
- Size: 203 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
---
title: Object Detection
emoji: 🖼
colorFrom: green
colorTo: purple
sdk: gradio
sdk_version: 5.5.0
app_file: app.py
pinned: false
short_description: Object detection via Gradio
---
# Object detection
Aim: AI-driven object detection (on COCO image dataset)
Machine learning models:
- facebook/detr-resnet-50,
- facebook/detr-resnet-101,
- hustvl/yolos-tiny,
- hustvl/yolos-small
### Table of contents:
- [Execution via command line](#1-execution-via-command-line)
- [Execution via User Interface ](#2-execution-via-user-interface)
- [Execution via Gradio client API](#3-execution-via-gradio-client-api)
- [Deployment on Hugging Face](#4-deployment-on-hugging-face)
- [Deployment on Docker Hub](#5-deployment-on-docker-hub)
## 1. Execution via command line
### 1.1. Use of torch library
> python detect_torch.py
### 1.2. Use of transformers library
> python detect_transformers.py
### 1.3. Use of HuggingFace pipeline library
> python detect_pipeline.py
## 2. Execution via User Interface
Use of Gradio library for web interface
Command line:
> python app.py
Note: The Gradio app should now be accessible at http://localhost:7860
## 3. Execution via Gradio client API
Note: Use of existing Gradio server (running locally, in a Docker container, or in the cloud as a HuggingFace space or AWS)
### 3.1. Creation of docker container
Command lines:
> sudo docker build -t gradio-app .
> sudo docker run -p 7860:7860 gradio-app
The Gradio app should now be accessible at http://localhost:7860
### 3.2. Direct inference via API
Command line:
> python inference_API.py
## 4. Deployment on Hugging Face
This web application is available on Hugging Face, via a Gradio space
URL: https://huggingface.co/spaces/cvachet/object_detection_gradio
## 5. Deployment on Docker Hub
This web application is available as a container on Docker Hub
URL: https://hub.docker.com/r/cvachet/object-detection-gradio