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import os, glob |
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from flask import Flask, request, render_template |
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from transformers import pipeline |
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from ultralytics import YOLO |
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app = Flask(__name__) |
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app.config['UPLOAD_FOLDER'] = 'static/uploads' |
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app.config['MARKED_FOLDER'] = 'static/marked' |
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PREDICT_FOLDER = os.path.join(app.config['MARKED_FOLDER'], 'predict') |
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os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True) |
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os.makedirs(PREDICT_FOLDER, exist_ok=True) |
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pipe = pipeline("image-classification", model="JorgeGIT/Finetuned-Leukemia-cell") |
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yolo_model = YOLO("runs/detect/leukemia-yolo-model/weights/best.pt") |
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def calculate_combined_risk(blast_risk, huggingface_score, age, sex): |
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score = 0.6 * blast_risk + 0.4 * huggingface_score |
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if age and int(age) > 60: |
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score += 5 |
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if sex == 'male': |
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score += 2 |
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return min(round(score, 1), 100) |
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@app.route('/', methods=['GET']) |
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def home(): |
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return render_template('index.html') |
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@app.route('/upload', methods=['GET', 'POST']) |
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def upload_file(): |
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if request.method == 'POST': |
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file = request.files.get('file') |
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age = request.form.get('age') |
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sex = request.form.get('sex') |
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if not file or file.filename == '' or not age or not sex: |
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return "กรุณากรอกข้อมูลให้ครบ" |
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filename = file.filename |
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filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename) |
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file.save(filepath) |
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results = yolo_model.predict( |
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source=filepath, |
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save=True, |
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project=app.config['MARKED_FOLDER'], |
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name='predict', |
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exist_ok=True |
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) |
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list_of_files = glob.glob(os.path.join(PREDICT_FOLDER, '*.jpg')) |
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latest_file = max(list_of_files, key=os.path.getctime) |
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marked_filename = os.path.relpath(latest_file, 'static').replace('\\', '/') |
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total_cells = len(results[0].boxes) |
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abnormal_cells = 0 |
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for box in results[0].boxes: |
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cls_id = int(box.cls[0].item()) |
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class_name = results[0].names[cls_id] |
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if 'blast' in class_name.lower(): |
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abnormal_cells += 1 |
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blast_risk = round((abnormal_cells / total_cells) * 100, 1) if total_cells else 0.0 |
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result = pipe(filepath) |
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lla_result = [ |
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{'label': 'โอกาสการเกิดโรค Leukemia = ', 'score': round(res['score'] * 1000, 1)} |
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for res in result if res['label'].lower() == 'lla' |
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] |
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huggingface_score = lla_result[0]['score'] if lla_result else 0.0 |
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combined_risk = calculate_combined_risk(blast_risk, huggingface_score, age, sex) |
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return render_template('result.html', |
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filename=filename, |
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marked_filename=marked_filename, |
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total_cells=total_cells, |
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abnormal_cells=abnormal_cells, |
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blast_risk=blast_risk, |
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huggingface_score=huggingface_score, |
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combined_risk=combined_risk, |
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age=age, |
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sex=sex |
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) |
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return render_template('upload.html') |
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if __name__ == '__main__': |
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app.run(host='0.0.0.0', port=7860) |
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