Delete app.py

app.py

@@ -1,403 +0,0 @@
-from fastapi import FastAPI, File, UploadFile
-from fastapi.responses import HTMLResponse
-from transformers import pipeline
-from PIL import Image, ImageDraw
-import numpy as np
-import io
-import uvicorn
-import base64
-
-app = FastAPI()
-
-# Chargement des modèles
-def load_models():
-    return {
-        "KnochenAuge": pipeline("object-detection", model="D3STRON/bone-fracture-detr"),
-        "KnochenWächter": pipeline("image-classification", model="Heem2/bone-fracture-detection-using-xray"),
-        "RöntgenMeister": pipeline("image-classification", 
-            model="nandodeomkar/autotrain-fracture-detection-using-google-vit-base-patch-16-54382127388")
-    }
-
-models = load_models()
-
-def translate_label(label):
-    translations = {
-        "fracture": "Knochenbruch",
-        "no fracture": "Kein Knochenbruch",
-        "normal": "Normal",
-        "abnormal": "Auffällig",
-        "F1": "Knochenbruch",
-        "NF": "Kein Knochenbruch"
-    }
-    return translations.get(label.lower(), label)
-
-def create_heatmap_overlay(image, box, score):
-    overlay = Image.new('RGBA', image.size, (0, 0, 0, 0))
-    draw = ImageDraw.Draw(overlay)
-    
-    x1, y1 = box['xmin'], box['ymin']
-    x2, y2 = box['xmax'], box['ymax']
-    
-    if score > 0.8:
-        fill_color = (255, 0, 0, 100)
-        border_color = (255, 0, 0, 255)
-    elif score > 0.6:
-        fill_color = (255, 165, 0, 100)
-        border_color = (255, 165, 0, 255)
-    else:
-        fill_color = (255, 255, 0, 100)
-        border_color = (255, 255, 0, 255)
-    
-    draw.rectangle([x1, y1, x2, y2], fill=fill_color)
-    draw.rectangle([x1, y1, x2, y2], outline=border_color, width=2)
-    
-    return overlay
-
-def draw_boxes(image, predictions):
-    result_image = image.copy().convert('RGBA')
-    
-    for pred in predictions:
-        box = pred['box']
-        score = pred['score']
-        
-        overlay = create_heatmap_overlay(image, box, score)
-        result_image = Image.alpha_composite(result_image, overlay)
-        
-        draw = ImageDraw.Draw(result_image)
-        temp = 36.5 + (score * 2.5)
-        label = f"{translate_label(pred['label'])} ({score:.1%} • {temp:.1f}°C)"
-        
-        text_bbox = draw.textbbox((box['xmin'], box['ymin']-20), label)
-        draw.rectangle(text_bbox, fill=(0, 0, 0, 180))
-        
-        draw.text(
-            (box['xmin'], box['ymin']-20),
-            label,
-            fill=(255, 255, 255, 255)
-        )
-    
-    return result_image
-
-def image_to_base64(image):
-    buffered = io.BytesIO()
-    image.save(buffered, format="PNG")
-    img_str = base64.b64encode(buffered.getvalue()).decode()
-    return f"data:image/png;base64,{img_str}"
-
-COMMON_STYLES = """
-    body {
-        font-family: system-ui, -apple-system, sans-serif;
-        background: #f0f2f5;
-        margin: 0;
-        padding: 20px;
-        color: #1a1a1a;
-    }
-    ::-webkit-scrollbar {
-        width: 8px;
-        height: 8px;
-    }
-    
-    ::-webkit-scrollbar-track {
-        background: transparent;
-    }
-    
-    ::-webkit-scrollbar-thumb {
-        background-color: rgba(156, 163, 175, 0.5);
-        border-radius: 4px;
-    }
-    
-    .container {
-        max-width: 1200px;
-        margin: 0 auto;
-        background: white;
-        padding: 20px;
-        border-radius: 10px;
-        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-    }
-    .button {
-        background: #2d2d2d;
-        color: white;
-        border: none;
-        padding: 12px 30px;
-        border-radius: 8px;
-        cursor: pointer;
-        font-size: 1.1em;
-        transition: all 0.3s ease;
-        position: relative;
-    }
-    .button:hover {
-        background: #404040;
-    }
-    @keyframes progress {
-        0% { width: 0; }
-        100% { width: 100%; }
-    }
-    .button-progress {
-        position: absolute;
-        bottom: 0;
-        left: 0;
-        height: 4px;
-        background: rgba(255, 255, 255, 0.5);
-        width: 0;
-    }
-    .button:active .button-progress {
-        animation: progress 2s linear forwards;
-    }
-    img {
-        max-width: 100%;
-        height: auto;
-        border-radius: 8px;
-    }
-    @keyframes blink {
-        0% { opacity: 1; }
-        50% { opacity: 0; }
-        100% { opacity: 1; }
-    }
-    #loading {
-        display: none;
-        color: white;
-        margin-top: 10px;
-        animation: blink 1s infinite;
-        text-align: center;
-    }
-"""
-
-@app.get("/", response_class=HTMLResponse)
-async def main():
-    content = f"""
-    <!DOCTYPE html>
-    <html>
-    <head>
-        <title>Fraktur Detektion</title>
-        <meta name="viewport" content="width=device-width, initial-scale=1.0">
-        <style>
-            {COMMON_STYLES}
-            
-            .upload-section {{
-                background: #2d2d2d;
-                padding: 40px;
-                border-radius: 12px;
-                margin: 20px 0;
-                text-align: center;
-                border: 2px dashed #404040;
-                transition: all 0.3s ease;
-                color: white;
-            }}
-            .upload-section:hover {{
-                border-color: #555;
-            }}
-            input[type="file"] {{
-                font-size: 1.1em;
-                margin: 20px 0;
-                color: white;
-            }}
-            input[type="file"]::file-selector-button {{
-                font-size: 1em;
-                padding: 10px 20px;
-                border-radius: 8px;
-                border: 1px solid #404040;
-                background: #2d2d2d;
-                color: white;
-                transition: all 0.3s ease;
-                cursor: pointer;
-            }}
-            input[type="file"]::file-selector-button:hover {{
-                background: #404040;
-            }}
-            .confidence-slider {{
-                width: 100%;
-                max-width: 300px;
-                margin: 20px auto;
-            }}
-            input[type="range"] {{
-                width: 100%;
-                height: 8px;
-                border-radius: 4px;
-                background: #404040;
-                outline: none;
-                transition: all 0.3s ease;
-                -webkit-appearance: none;
-            }}
-            input[type="range"]::-webkit-slider-thumb {{
-                -webkit-appearance: none;
-                width: 20px;
-                height: 20px;
-                border-radius: 50%;
-                background: white;
-                cursor: pointer;
-                border: none;
-            }}
-        </style>
-    </head>
-    <body>
-        <div class="container">
-            <div class="upload-section">
-                <form action="/analyze" method="post" enctype="multipart/form-data" onsubmit="document.getElementById('loading').style.display = 'block';">
-                    <div>
-                        <input type="file" name="file" accept="image/*" required>
-                    </div>
-                    <div class="confidence-slider">
-                        <label for="threshold">Konfidenzschwelle: <span id="thresholdValue">0.60</span></label>
-                        <input type="range" id="threshold" name="threshold" 
-                               min="0" max="1" step="0.05" value="0.60" 
-                               oninput="document.getElementById('thresholdValue').textContent = parseFloat(this.value).toFixed(2)">
-                    </div>
-                    <button type="submit" class="button">
-                        Analysieren
-                        <div class="button-progress"></div>
-                    </button>
-                    <div id="loading">Loading...</div>
-                </form>
-            </div>
-        </div>
-    </body>
-    </html>
-    """
-    return content
-
-@app.post("/analyze", response_class=HTMLResponse)
-async def analyze_file(file: UploadFile = File(...)):
-    try:
-        contents = await file.read()
-        image = Image.open(io.BytesIO(contents))
-        
-        predictions_watcher = models["KnochenWächter"](image)
-        predictions_master = models["RöntgenMeister"](image)
-        predictions_locator = models["KnochenAuge"](image)
-        
-        filtered_preds = [p for p in predictions_locator if p['score'] >= 0.6]
-        if filtered_preds:
-            result_image = draw_boxes(image, filtered_preds)
-        else:
-            result_image = image
-
-        result_image_b64 = image_to_base64(result_image)
-        
-        results_html = f"""
-        <!DOCTYPE html>
-        <html>
-        <head>
-            <title>Ergebnisse</title>
-            <meta name="viewport" content="width=device-width, initial-scale=1.0">
-            <style>
-                {COMMON_STYLES}
-                
-                .results-grid {{
-                    display: grid;
-                    grid-template-columns: 1fr 1fr;
-                    gap: 20px;
-                    margin-top: 20px;
-                }}
-                .result-box {{
-                    background: white;
-                    padding: 20px;
-                    border-radius: 12px;
-                    margin: 10px 0;
-                    border: 1px solid #e9ecef;
-                }}
-                .score-high {{ 
-                    color: #0066cc; 
-                    font-weight: bold;
-                }}
-                
-                .score-medium {{ 
-                    color: #ffa500; 
-                    font-weight: bold;
-                }}
-                .back-button {{
-                    display: inline-block;
-                    text-decoration: none;
-                    margin-top: 20px;
-                }}
-                h3 {{
-                    color: #0066cc;
-                    margin-top: 0;
-                }}
-                @media (max-width: 768px) {{
-                    .results-grid {{
-                        grid-template-columns: 1fr;
-                    }}
-                }}
-            </style>
-        </head>
-        <body>
-            <div class="container">
-                <div class="results-grid">
-                    <div>
-                        <div class="result-box"><h3>KnochenWächter</h3>
-        """
-        
-        for pred in predictions_watcher:
-            confidence_class = "score-high" if pred['score'] > 0.7 else "score-medium"
-            results_html += f"""
-                <div>
-                    <span class="{confidence_class}">{pred['score']:.1%}</span> - 
-                    {translate_label(pred['label'])}
-                </div>
-            """
-        results_html += "</div>"
-        
-        results_html += "<div class='result-box'><h3>RöntgenMeister</h3>"
-        for pred in predictions_master:
-            confidence_class = "score-high" if pred['score'] > 0.7 else "score-medium"
-            results_html += f"""
-                <div>
-                    <span class="{confidence_class}">{pred['score']:.1%}</span> - 
-                    {translate_label(pred['label'])}
-                </div>
-            """
-        results_html += "</div></div>"
-        
-        results_html += f"""
-                    <div class='result-box'>
-                        <h3>Fraktur Lokalisation</h3>
-                        <img src="{result_image_b64}" alt="Analyzed image">
-                    </div>
-                </div>
-                
-                <a href="/" class="button back-button">
-                    ← Zurück
-                    <div class="button-progress"></div>
-                </a>
-            </div>
-        </body>
-        </html>
-        """
-        
-        return results_html
-        
-    except Exception as e:
-        return f"""
-        <!DOCTYPE html>
-        <html>
-        <head>
-            <title>Fehler</title>
-            <meta name="viewport" content="width=device-width, initial-scale=1.0">
-            <style>
-                {COMMON_STYLES}
-                .error-box {{
-                    background: #fee2e2;
-                    border: 1px solid #ef4444;
-                    padding: 20px;
-                    border-radius: 8px;
-                    margin: 20px 0;
-                }}
-            </style>
-        </head>
-        <body>
-            <div class="container">
-                <div class="error-box">
-                    <h3>Fehler</h3>
-                    <p>{str(e)}</p>
-                </div>
-                <a href="/" class="button back-button">
-                    ← Zurück
-                    <div class="button-progress"></div>
-                </a>
-            </div>
-        </body>
-        </html>
-        """
-
-if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=7860)