Delete models/app.py

models/app.py

@@ -1,153 +0,0 @@
-# app.py
-
-import os
-import torch
-from flask import Flask, request, jsonify, render_template
-from flask_cors import CORS
-from werkzeug.utils import secure_filename
-from ultralytics import YOLO
-from dotenv import load_dotenv
-
-# Load environment variables from .env file
-load_dotenv()
-
-app = Flask(__name__)
-
-# Enable CORS for all routes
-CORS(app)
-
-# --- Configuration ---
-UPLOAD_FOLDER = 'static/uploads'
-MODELS_FOLDER = 'models'
-ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg'}
-
-# --- NEW: Load model names from .env file, with fallback defaults ---
-MODEL_1_NAME = os.getenv('MODEL_1_NAME', 'best.pt')
-MODEL_2_NAME = os.getenv('MODEL_2_NAME', 'tyre_alloy.pt') # New model for Tyre/Alloy
-
-MODEL_1_PATH = os.path.join(MODELS_FOLDER, MODEL_1_NAME)
-MODEL_2_PATH = os.path.join(MODELS_FOLDER, MODEL_2_NAME)
-
-app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
-os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
-os.makedirs(MODELS_FOLDER, exist_ok=True)
-os.makedirs('templates', exist_ok=True)
-
-# --- Determine Device ---
-device = "cuda" if torch.cuda.is_available() else "cpu"
-print(f"Using device: {device}")
-
-# --- NEW: Load multiple YOLO Models ---
-model1, model2 = None, None
-
-# Load Model 1
-try:
-    if not os.path.exists(MODEL_1_PATH):
-        print(f"Warning: Model file not found at {MODEL_1_PATH}")
-    else:
-        model1 = YOLO(MODEL_1_PATH)
-        model1.to(device)
-        print(f"Successfully loaded model '{MODEL_1_NAME}' on {device}.")
-except Exception as e:
-    print(f"Error loading Model 1 ({MODEL_1_NAME}): {e}")
-
-# Load Model 2
-try:
-    if not os.path.exists(MODEL_2_PATH):
-        print(f"Warning: Model file not found at {MODEL_2_PATH}")
-    else:
-        model2 = YOLO(MODEL_2_PATH)
-        model2.to(device)
-        print(f"Successfully loaded model '{MODEL_2_NAME}' on {device}.")
-except Exception as e:
-    print(f"Error loading Model 2 ({MODEL_2_NAME}): {e}")
-
-
-def allowed_file(filename):
-    """Checks if a file's extension is in the ALLOWED_EXTENSIONS set."""
-    return '.' in filename and \
-           filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
-
-def run_inference(model, filepath):
-    """Helper function to run inference and format the result."""
-    if model is None:
-        return None # Return None if the model isn't loaded
-
-    results = model(filepath)
-    result = results[0]
-    probs = result.probs
-    top1_index = probs.top1
-    top1_confidence = float(probs.top1conf)
-    class_name = model.names[top1_index]
-    
-    return {
-        "class": class_name,
-        "confidence": top1_confidence
-    }
-
-@app.route('/')
-def home():
-    """Serve the main HTML page."""
-    return render_template('index.html')
-
-@app.route('/predict', methods=['POST'])
-def predict():
-    """
-    Endpoint to receive an image and run classification based on the requested model type.
-    """
-    # 1. --- File Validation ---
-    if 'file' not in request.files:
-        return jsonify({"error": "No file part in the request"}), 400
-    file = request.files['file']
-    if file.filename == '':
-        return jsonify({"error": "No selected file"}), 400
-    if not file or not allowed_file(file.filename):
-        return jsonify({"error": "File type not allowed"}), 400
-
-    # --- NEW: Get the model type from the form data ---
-    model_type = request.form.get('model_type', 'model1') # default to model1
-
-    # 2. --- Save the File Temporarily ---
-    filename = secure_filename(file.filename)
-    filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
-    file.save(filepath)
-
-    # 3. --- Perform Inference based on model_type ---
-    try:
-        if model_type == 'model1':
-            if model1 is None:
-                return jsonify({"error": f"Model '{MODEL_1_NAME}' is not loaded. Check server logs."}), 500
-            prediction = run_inference(model1, filepath)
-            return jsonify(prediction)
-
-        elif model_type == 'model2':
-            if model2 is None:
-                return jsonify({"error": f"Model '{MODEL_2_NAME}' is not loaded. Check server logs."}), 500
-            prediction = run_inference(model2, filepath)
-            return jsonify(prediction)
-
-        elif model_type == 'combined':
-            if model1 is None or model2 is None:
-                 return jsonify({"error": "One or more models required for combined mode are not loaded. Check server logs."}), 500
-            
-            pred1 = run_inference(model1, filepath)
-            pred2 = run_inference(model2, filepath)
-            
-            combined_prediction = {
-                "model1_result": pred1,
-                "model2_result": pred2
-            }
-            return jsonify(combined_prediction)
-
-        else:
-            return jsonify({"error": "Invalid model type specified"}), 400
-
-    except Exception as e:
-        return jsonify({"error": f"An error occurred during inference: {str(e)}"}), 500
-    finally:
-        # 4. --- Cleanup ---
-        if os.path.exists(filepath):
-            os.remove(filepath)
-
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=7860, debug=True)