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Update app.py
Browse files
app.py
CHANGED
@@ -2,7 +2,9 @@ from fastapi import FastAPI, File, UploadFile
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from fastapi.responses import HTMLResponse
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from transformers import pipeline
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from PIL import Image, ImageDraw
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import io
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import base64
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app = FastAPI()
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@@ -67,7 +69,12 @@ def draw_boxes(image, predictions):
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text_bbox = draw.textbbox((box['xmin'], box['ymin']-20), label)
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draw.rectangle(text_bbox, fill=(0, 0, 0, 180))
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return result_image
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@@ -77,116 +84,121 @@ def image_to_base64(image):
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img_str = base64.b64encode(buffered.getvalue()).decode()
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return f"data:image/png;base64,{img_str}"
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body {
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font-family: system-ui, -apple-system, sans-serif;
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background: #
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margin: 0;
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padding: 20px;
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color: #
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}
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.container {
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max-width: 1200px;
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margin: 0 auto;
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background:
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padding: 20px;
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border-radius: 10px;
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box-shadow: 0 4px
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}
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.upload-section {
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background: #2d3748;
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padding: 40px;
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border-radius: 12px;
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margin: 20px 0;
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text-align: center;
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border: 2px dashed #4a5568;
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}
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/* Animation de chargement */
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@keyframes loading {
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0% { background-position: 200% 0; }
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100% { background-position: -200% 0; }
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}
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.button {
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background: #
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color: white;
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border: none;
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padding: 12px 30px;
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border-radius: 8px;
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cursor: pointer;
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font-size: 1.1em;
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}
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.button:
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background:
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background-size: 200% 100%;
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animation: loading 2s infinite linear;
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}
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color: #e2e8f0;
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}
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input[type="file"]::file-selector-button {
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font-size: 1em;
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padding: 10px 20px;
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border-radius: 8px;
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border: 1px solid #4a5568;
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background: #2d3748;
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color: #e2e8f0;
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cursor: pointer;
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}
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}
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}
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font-weight: bold;
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}
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.score-medium {
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color: #ed8936;
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font-weight: bold;
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}
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img {
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max-width: 100%;
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border-radius: 8px;
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box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
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}
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h3 {
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color: #63b3ed;
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margin-top: 0;
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}
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.results-grid {
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display: grid;
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grid-template-columns: 1fr 1fr;
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gap: 20px;
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margin-top: 20px;
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}
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@media (max-width: 768px) {
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.results-grid {
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grid-template-columns: 1fr;
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}
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}
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"""
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@@ -198,15 +210,86 @@ async def main():
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<head>
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<title>Fraktur Detektion</title>
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<style>
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</head>
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<body>
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<div class="container">
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<div class="upload-section">
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<form action="/analyze" method="post" enctype="multipart/form-data">
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<
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</form>
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</div>
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</div>
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@@ -226,7 +309,11 @@ async def analyze_file(file: UploadFile = File(...)):
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predictions_locator = models["KnochenAuge"](image)
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filtered_preds = [p for p in predictions_locator if p['score'] >= 0.6]
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result_image_b64 = image_to_base64(result_image)
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results_html = f"""
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@@ -235,7 +322,57 @@ async def analyze_file(file: UploadFile = File(...)):
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<head>
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<title>Ergebnisse</title>
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<style>
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</head>
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<body>
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<div class="container">
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</div>
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</div>
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<a href="/" class="button"
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</div>
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</body>
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</html>
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<head>
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<title>Fehler</title>
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<style>
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</head>
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<body>
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<div class="container">
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<div class="
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<h3>Fehler</h3>
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<p>{str(e)}</p>
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</div>
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<a href="/" class="button"
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</div>
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</body>
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</html>
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"""
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=7860)
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from fastapi.responses import HTMLResponse
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from transformers import pipeline
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from PIL import Image, ImageDraw
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import numpy as np
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import io
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import uvicorn
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import base64
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app = FastAPI()
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text_bbox = draw.textbbox((box['xmin'], box['ymin']-20), label)
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draw.rectangle(text_bbox, fill=(0, 0, 0, 180))
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draw.text(
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(box['xmin'], box['ymin']-20),
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label,
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fill=(255, 255, 255, 255)
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)
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return result_image
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img_str = base64.b64encode(buffered.getvalue()).decode()
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return f"data:image/png;base64,{img_str}"
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# Styles communs pour les deux pages
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COMMON_STYLES = """
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:root {
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color-scheme: light dark;
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}
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@media (prefers-color-scheme: dark) {
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body {
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background: #1a1a1a !important;
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color: #ffffff !important;
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}
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.container {
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background: #2d2d2d !important;
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}
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.result-box, .upload-section {
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background: #363636 !important;
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border-color: #555 !important;
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}
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.button {
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background: #0066cc !important;
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}
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input[type="file"]::file-selector-button {
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background: #444 !important;
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color: #fff !important;
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border-color: #555 !important;
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}
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input[type="range"] {
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background: #444 !important;
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}
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.button-progress {
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background: rgba(255, 255, 255, 0.2) !important;
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}
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}
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body {
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font-family: system-ui, -apple-system, sans-serif;
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background: #f0f2f5;
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margin: 0;
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padding: 20px;
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color: #1a1a1a;
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}
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/* Scrollbar personnalisée */
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::-webkit-scrollbar {
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width: 8px;
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height: 8px;
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}
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::-webkit-scrollbar-track {
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background: transparent;
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}
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::-webkit-scrollbar-thumb {
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background-color: rgba(156, 163, 175, 0.5);
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border-radius: 4px;
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}
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@media (prefers-color-scheme: dark) {
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::-webkit-scrollbar-thumb {
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background-color: rgba(75, 85, 99, 0.5);
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}
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}
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.container {
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max-width: 1200px;
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margin: 0 auto;
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background: white;
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padding: 20px;
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border-radius: 10px;
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box-shadow: 0 2px 4px rgba(0,0,0,0.1);
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}
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.button {
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background: #0066cc;
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color: white;
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border: none;
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padding: 12px 30px;
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border-radius: 8px;
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cursor: pointer;
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font-size: 1.1em;
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transition: all 0.3s ease;
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position: relative;
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}
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.button:hover {
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background: #0052a3;
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}
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/* Nouvelle barre de progression */
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.button {
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position: relative;
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}
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@keyframes progress {
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0% { width: 0; }
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100% { width: 100%; }
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}
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.button-progress {
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position: absolute;
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bottom: 0;
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left: 0;
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height: 4px;
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background: rgba(255, 255, 255, 0.5);
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width: 0;
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}
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.button:active .button-progress {
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animation: progress 2s linear forwards;
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}
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img {
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max-width: 100%;
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height: auto;
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border-radius: 8px;
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}
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"""
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<head>
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<title>Fraktur Detektion</title>
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<style>
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{COMMON_STYLES}
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.upload-section {{
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background: #f8f9fa;
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padding: 40px;
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border-radius: 12px;
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margin: 20px 0;
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text-align: center;
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border: 2px dashed #ccc;
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transition: all 0.3s ease;
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}}
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.upload-section:hover {{
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border-color: #0066cc;
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}}
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input[type="file"] {{
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font-size: 1.1em;
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margin: 20px 0;
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}}
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input[type="file"]::file-selector-button {{
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font-size: 1em;
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padding: 10px 20px;
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border-radius: 8px;
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border: 1px solid #ccc;
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background: #f8f9fa;
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transition: all 0.3s ease;
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cursor: pointer;
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}}
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input[type="file"]::file-selector-button:hover {{
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background: #e9ecef;
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}}
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.confidence-slider {{
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width: 100%;
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max-width: 300px;
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margin: 20px auto;
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}}
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input[type="range"] {{
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width: 100%;
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height: 8px;
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border-radius: 4px;
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background: #e9ecef;
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outline: none;
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transition: all 0.3s ease;
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-webkit-appearance: none;
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}}
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input[type="range"]::-webkit-slider-thumb {{
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-webkit-appearance: none;
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width: 20px;
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height: 20px;
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border-radius: 50%;
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background: #0066cc;
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cursor: pointer;
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border: none;
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}}
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</style>
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</head>
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<body>
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<div class="container">
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<div class="upload-section">
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<form action="/analyze" method="post" enctype="multipart/form-data">
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<div>
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<input type="file" name="file" accept="image/*" required>
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+
</div>
|
283 |
+
<div class="confidence-slider">
|
284 |
+
<label for="threshold">Konfidenzschwelle: <span id="thresholdValue">0.60</span></label>
|
285 |
+
<input type="range" id="threshold" name="threshold"
|
286 |
+
min="0" max="1" step="0.05" value="0.60"
|
287 |
+
oninput="document.getElementById('thresholdValue').textContent = parseFloat(this.value).toFixed(2)">
|
288 |
+
</div>
|
289 |
+
<button type="submit" class="button">
|
290 |
+
Analysieren
|
291 |
+
<div class="button-progress"></div>
|
292 |
+
</button>
|
293 |
</form>
|
294 |
</div>
|
295 |
</div>
|
|
|
309 |
predictions_locator = models["KnochenAuge"](image)
|
310 |
|
311 |
filtered_preds = [p for p in predictions_locator if p['score'] >= 0.6]
|
312 |
+
if filtered_preds:
|
313 |
+
result_image = draw_boxes(image, filtered_preds)
|
314 |
+
else:
|
315 |
+
result_image = image
|
316 |
+
|
317 |
result_image_b64 = image_to_base64(result_image)
|
318 |
|
319 |
results_html = f"""
|
|
|
322 |
<head>
|
323 |
<title>Ergebnisse</title>
|
324 |
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
325 |
+
<style>
|
326 |
+
{COMMON_STYLES}
|
327 |
+
|
328 |
+
.results-grid {{
|
329 |
+
display: grid;
|
330 |
+
grid-template-columns: 1fr 1fr;
|
331 |
+
gap: 20px;
|
332 |
+
margin-top: 20px;
|
333 |
+
}}
|
334 |
+
|
335 |
+
.result-box {{
|
336 |
+
background: #f8f9fa;
|
337 |
+
padding: 20px;
|
338 |
+
border-radius: 12px;
|
339 |
+
margin: 10px 0;
|
340 |
+
border: 1px solid #e9ecef;
|
341 |
+
}}
|
342 |
+
|
343 |
+
.score-high {{
|
344 |
+
color: #0066cc;
|
345 |
+
font-weight: bold;
|
346 |
+
}}
|
347 |
+
|
348 |
+
.score-medium {{
|
349 |
+
color: #ffa500;
|
350 |
+
font-weight: bold;
|
351 |
+
}}
|
352 |
+
|
353 |
+
.back-button {{
|
354 |
+
display: inline-block;
|
355 |
+
text-decoration: none;
|
356 |
+
margin-top: 20px;
|
357 |
+
}}
|
358 |
+
|
359 |
+
h3 {{
|
360 |
+
color: #0066cc;
|
361 |
+
margin-top: 0;
|
362 |
+
}}
|
363 |
+
|
364 |
+
@media (prefers-color-scheme: dark) {{
|
365 |
+
h3 {{
|
366 |
+
color: #66b3ff;
|
367 |
+
}}
|
368 |
+
}}
|
369 |
+
|
370 |
+
@media (max-width: 768px) {{
|
371 |
+
.results-grid {{
|
372 |
+
grid-template-columns: 1fr;
|
373 |
+
}}
|
374 |
+
}}
|
375 |
+
</style>
|
376 |
</head>
|
377 |
<body>
|
378 |
<div class="container">
|
|
|
412 |
</div>
|
413 |
</div>
|
414 |
|
415 |
+
<a href="/" class="button back-button">
|
416 |
+
← Zurück
|
417 |
+
<div class="button-progress"></div>
|
418 |
+
</a>
|
419 |
</div>
|
420 |
</body>
|
421 |
</html>
|
|
|
430 |
<head>
|
431 |
<title>Fehler</title>
|
432 |
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
433 |
+
<style>
|
434 |
+
{COMMON_STYLES}
|
435 |
+
.error-box {{
|
436 |
+
background: #fee2e2;
|
437 |
+
border: 1px solid #ef4444;
|
438 |
+
padding: 20px;
|
439 |
+
border-radius: 8px;
|
440 |
+
margin: 20px 0;
|
441 |
+
}}
|
442 |
+
@media (prefers-color-scheme: dark) {{
|
443 |
+
.error-box {{
|
444 |
+
background: #471818;
|
445 |
+
border-color: #dc2626;
|
446 |
+
}}
|
447 |
+
}}
|
448 |
+
</style>
|
449 |
</head>
|
450 |
<body>
|
451 |
<div class="container">
|
452 |
+
<div class="error-box">
|
453 |
<h3>Fehler</h3>
|
454 |
<p>{str(e)}</p>
|
455 |
</div>
|
456 |
+
<a href="/" class="button back-button">
|
457 |
+
← Zurück
|
458 |
+
<div class="button-progress"></div>
|
459 |
+
</a>
|
460 |
</div>
|
461 |
</body>
|
462 |
</html>
|
463 |
"""
|
464 |
|
465 |
if __name__ == "__main__":
|
|
|
466 |
uvicorn.run(app, host="0.0.0.0", port=7860)
|