app.py

import os
import numpy as np
import tensorflow as tf
from flask import Flask, render_template, request
from werkzeug.utils import secure_filename
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing import image

app = Flask(__name__)

# Load mô hình đã huấn luyện
model = load_model('ml/best_model.keras')
class_names = ['butterfly', 'cat', 'chicken', 'cow', 'dog', 'elephant', 'hourse', 'sheep', 'spider', 'squirrel']

UPLOAD_FOLDER = 'static/uploads'
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER

def preprocess_image(img_path):
    """Tiền xử lý ảnh."""
    img = image.load_img(img_path, target_size=(224, 224))
    img_array = image.img_to_array(img) / 255.0  # Chuẩn hóa
    img_array = np.expand_dims(img_array, axis=0)
    return img_array

@app.route("/", methods=["GET", "POST"])
def upload_folder():
    if request.method == "POST":
        if "file" not in request.files:
            return render_template("index.html", error="No files uploaded")

        files = request.files.getlist("file")  # Nhận danh sách ảnh tải lên
        if not files or files[0].filename == "":
            return render_template("index.html", error="No valid images selected")

        # Tạo thư mục nếu chưa tồn tại
        extract_folder = os.path.join(app.config["UPLOAD_FOLDER"], "extracted")
        os.makedirs(extract_folder, exist_ok=True)

        uploaded_images = []
        predictions = []

        for file in files:
            if file.filename.lower().endswith((".png", ".jpg", ".jpeg")):
                img_path = os.path.join(extract_folder, secure_filename(file.filename))
                file.save(img_path)

                # Dự đoán ảnh
                img_array = preprocess_image(img_path)
                prediction = model.predict(img_array)[0]
                predicted_class = class_names[np.argmax(prediction)]
                confidence = np.max(prediction) * 100

                uploaded_images.append(img_path)
                predictions.append({"class": predicted_class, "confidence": confidence})

        return render_template("result.html", images=uploaded_images, predictions=predictions)

    return render_template("index.html")

if __name__ == "__main__":
    app.run(debug=True)