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https://github.com/ajay-dhangar/nothotdog
This project uses the Hugging Face API to detect whether an image contains a hot dog or not.
https://github.com/ajay-dhangar/nothotdog
ai not-hot-dog not-hotdog project python3
Last synced: 28 days ago
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This project uses the Hugging Face API to detect whether an image contains a hot dog or not.
- Host: GitHub
- URL: https://github.com/ajay-dhangar/nothotdog
- Owner: ajay-dhangar
- Created: 2024-09-18T06:42:29.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-09-18T07:36:49.000Z (4 months ago)
- Last Synced: 2024-12-06T22:52:16.292Z (28 days ago)
- Topics: ai, not-hot-dog, not-hotdog, project, python3
- Language: HTML
- Homepage:
- Size: 127 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Not Hot Dog
## Detect "Not Hot Dogs" with hugging face API.
**Prerequisites:** *[Hugging Face](https://huggingface.co/), HTML, Python Fundamentals*
**Project Description:** This project uses the Hugging Face API to detect whether an image contains a hot dog or not. The API uses a pre-trained model to classify the image as either a hot dog or not a hot dog. The project also includes a simple HTML interface to upload an image and display the results.
**Let's get started! ðŸŒ**
### Setting Up
1. Create a new directory named nothotdog. This is where our project will live.
for example:
```bash
mkdir nothotdog
```
2. Change into the nothotdog directory.
```bash
cd nothotdog
```
3. Create a new Python virtual environment.
> *Let's create a virtual environment or venv, which is an isolated environment that contains a Python installation in addition to other packages. If you want to learn more check out this [link](https://docs.python.org/3/tutorial/venv.html).*
```bash
python3 -m venv .venv
```
4. Activate the virtual environment.
```bash
source venv/bin/activate
```
5. Install Flask
> *Now we are going to install Flask, which is a web framework in Python that makes it easy create to web applications and APIs. You can read more about it [here](https://flask.palletsprojects.com/en/2.2.x/).*
```bash
python -m pip install flask
```
6. Install Dotenv
> *Dotenv is a Python module that reads key-value pairs from a .env file and can set them as environment variables. You can read more about it [here](https://pypi.org/project/python-dotenv/).*
```bash
python -m pip install python-dotenv
```
7. Install Requests
> *Requests is a Python module that allows you to send HTTP requests using Python. You can read more about it [here](https://pypi.org/project/requests/).*
```bash
python -m pip install requests
```
8. Create a templates folder for our HTML
```bash
mkdir templates
```
> *In Flask, if we are going to have HTML files we typically store them in a folder called templates so Flask is able to find them. Create a folder called templates, which should end up looking like this:*
```bash
nothotdog
├── templates
└── venv
```
9. Create a file called `index.html`
```bash
touch templates/index.html
```
10. Add the HTML code
```html
Hot dog or Not Hot dog?
body {
font-family: Arial, sans-serif;
text-align: center;
background-color: #f0f0f0;
margin: 0;
padding: 0;
}
h1 {
margin-top: 50px;
color: #333;
font-size: 2.5rem;
}
form {
background-color: #fff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
width: 100%;
max-width: 400px;
margin: 20px auto;
}
input[type="file"] {
margin-bottom: 20px;
padding: 10px;
border-radius: 4px;
border: 1px solid #ccc;
width: 100%;
}
input[type="submit"] {
background-color: #4caf50;
color: white;
padding: 14px 20px;
margin: 8px 0;
border: none;
cursor: pointer;
border-radius: 4px;
width: 100%;
font-size: 1rem;
}
input[type="submit"]:hover {
background-color: #45a049;
}
Hot dog or Not Hot dog?
Upload an image:
```
11. Create a file called `web.py`
```bash
touch web.py
```
12. Add the Python code
```python
from flask import Flask, render_template, request, jsonify
import requests
import json
import os
from dotenv import load_dotenv
load_dotenv()
API_URL = os.getenv("HUGGING_FACE_API_URL")
headers = {'Authorization': f'Bearer {os.getenv("HUGGING_FACE_API_KEY")}'}
app = Flask(__name__)
def query(data):
response = requests.request('POST', API_URL, headers=headers, data=data)
return json.loads(response.content.decode('utf-8'))
@app.route('/')
def index():
return render_template('./index.html')
@app.route('/upload', methods=['POST'])
def upload():
file = request.files['file1']
modeldata = query(file)
return jsonify(modeldata)
app.run(host='0.0.0.0', port=81)
```
13. Create a `.env` file
```bash
touch .env
```
14. Add the API URL and API Key to the `.env` file
```bash
HUGGING_FACE_API_URL=https://api-inference.huggingface.co/models/simon-mooney/not-hot-dog
HUGGING_FACE_API_KEY=
```
> ***Note:** HUGGING_FACE_API_KEY=, ading in your API key and URL. This is where we place the hugging face data to allow us to use hugging face's models.*
>
> *You can get your API key by signing up for a free account at [Hugging Face](https://huggingface.co/). and create a token https://huggingface.co/settings/tokens.*
15. Now run the project.
```bash
python web.py
```
16. Open your browser
```bash
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:81
* Running on http://192.168.71.231:81
```
> *Open your browser and go to http://127.0.0.1:81 or http://192.168.71.231:81.
17. Upload an image
> *You can now upload an image and see if it is a hot dog or not a hot dog.*
> *You should see the results displayed on the screen.*
### Conclusion
Congratulations! You have successfully created a project that uses the Hugging Face API to detect whether an image contains a hot dog or not. You have also created a simple HTML interface to upload an image and display the results. You can now use this project to classify images as hot dogs or not hot dogs. ðŸŒ