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from fastapi import FastAPI, File, UploadFile, HTTPException
from fastapi.responses import HTMLResponse
from transformers import pipeline
from PIL import Image
import io
app = FastAPI()
# Load the image classification pipeline
pipe = pipeline("image-classification", model="mateoluksenberg/dit-base-Classifier_CM05")
@app.post("/classify/")
async def classify_image(file: UploadFile = File(...)):
try:
# Read the file contents into a PIL image
image = Image.open(file.file).convert('RGB')
# Perform image classification
result = pipe(image)
# Overall result summary
overall_result = str(result)
# Add overall result as comment to the top result
result_with_comment = {
"label": result[0]['label'],
"score": result[0]['score'],
}
return {"classification_result": result_with_comment, "overall_result": overall_result} # Return the top prediction with comment and overall summary
except Exception as e:
# Handle exceptions, for example: file not found, image format issues, etc.
raise HTTPException(status_code=500, detail=f"Error processing image: {str(e)}")
@app.get("/", response_class=HTMLResponse)
async def home():
html_content = """
<!DOCTYPE html>
<html>
<head>
<title>Image Classification</title>
<style>
body {
font-family: Arial, sans-serif;
background-color: #f0f0f0;
margin: 0;
padding: 0;
display: flex;
justify-content: center;
align-items: center;
height: 100vh;
flex-direction: column;
}
h1 {
color: #333;
}
form {
margin: 20px 0;
padding: 20px;
background: #fff;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
border-radius: 8px;
}
input[type="file"] {
margin-bottom: 10px;
}
button {
background-color: #4CAF50;
color: white;
border: none;
padding: 10px 20px;
text-align: center;
text-decoration: none;
display: inline-block;
font-size: 16px;
border-radius: 5px;
cursor: pointer;
}
button:hover {
background-color: #45a049;
}
#result, #overall-results {
margin-top: 20px;
padding: 20px;
background: #fff;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
border-radius: 8px;
max-width: 500px;
word-wrap: break-word;
}
</style>
</head>
<body>
<h1>Upload an Image for Classification</h1>
<form id="upload-form" enctype="multipart/form-data">
<input type="file" id="file" name="file" accept="image/*" required />
<button type="submit">Upload</button>
</form>
<div id="result"></div>
<div id="overall-results"></div>
<script>
const form = document.getElementById('upload-form');
form.addEventListener('submit', async (e) => {
e.preventDefault();
const fileInput = document.getElementById('file');
const formData = new FormData();
formData.append('file', fileInput.files[0]);
const response = await fetch('/classify/', {
method: 'POST',
body: formData
});
const result = await response.json();
const resultDiv = document.getElementById('result');
const overallResultsDiv = document.getElementById('overall-results');
if (response.ok) {
resultDiv.innerHTML = `<h2>Top Classification Result:</h2><p>${JSON.stringify(result.classification_result)}</p>`;
overallResultsDiv.innerHTML = `<h2>All Results:</h2><p>${result.overall_result}</p>`;
} else {
resultDiv.innerHTML = `<h2>Error:</h2><p>${result.detail}</p>`;
overallResultsDiv.innerHTML = '';
}
});
</script>
</body>
</html>
"""
return HTMLResponse(content=html_content)
# Sample usage:
# 1. Start the FastAPI server
# 2. Open the browser and navigate to the root URL to upload an image and see the classification result
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