app.py

import requests
from io import BytesIO
from tensorflow.keras.models import load_model

from flask import Flask, render_template, request, jsonify, url_for, redirect, session
from tensorflow.keras.models import load_model
import cv2
import numpy as np
import os
from flask_babel import Babel
import gdown   # 🔹 for downloading model from Google Drive

# ---------------------- FLASK SETUP ----------------------

app = Flask(
    __name__,
    template_folder="templates",
    static_folder="static"
)

app.config['SECRET_KEY'] = 'a-very-secret-key-for-sessions'
app.config['LANGUAGES'] = {'en': 'English', 'hi': 'हिन्दी'}

# ---------------------- LANGUAGE SETUP ----------------------

def get_locale():
    return session.get('language', 'en')

babel = Babel(app, locale_selector=get_locale)

@app.route('/language/<language>')
def set_language(language=None):
    session['language'] = language
    return redirect(request.referrer)

# ---------------------- MODEL SETUP ----------------------
import gdown
import os
from tensorflow.keras.models import load_model

MODEL_PATH = "pearl_millet_ergot_model.h5"
DRIVE_FILE_ID = "1lzwncCGFtwmWSOsZwRVbZICEcPs1y0sI"
MODEL_URL = f"https://drive.google.com/uc?id={DRIVE_FILE_ID}"

def load_remote_model():
    """Download and load the model from Google Drive."""
    print("⏬ Downloading model from Google Drive...")
    gdown.download(MODEL_URL, MODEL_PATH, quiet=False)
    print("📦 Loading model into memory...")
    model = load_model(MODEL_PATH)
    print("✅ Model loaded successfully!")
    return model

# Load model on demand
model = load_remote_model()



# ---------------------- IMAGE PROCESSING ----------------------

def preprocess_image(image_path):
    img = cv2.imread(image_path)
    img = cv2.resize(img, (224, 224))
    img = img.astype("float32") / 255.0
    img = np.expand_dims(img, axis=0)
    return img

# ---------------------- HELPER FUNCTIONS ----------------------
from flask_babel import _

def get_severity(conf):
    if conf <= 10:
        return "Mild"
    elif conf <= 15:
        return "Moderate"
    else:
        return "High"


def get_risk(severity):
    if severity == "Mild":
        return "Low"
    elif severity == "Moderate":
        return "Medium"
    else:
        return "Critical"

# ---------------------- ROUTES ----------------------

@app.route("/")
def home():
    return render_template("index.html")

@app.route("/about_ergot")
def about_ergot():
    return render_template("about_ergot.html")

@app.route("/identify")
def identify():
    return render_template("identify.html")

@app.route("/faq")
def faq():
    return render_template("faq.html")

@app.route("/official_insights")
def official_insights():
    return render_template("official_insights.html")

@app.route("/contact")
def contact():
    return render_template("contact.html")

@app.route("/results_healthy")
def results_healthy():
    return render_template(
        "results_healthy.html",
        result=session.get('result'),
        confidence=session.get('confidence'),
        filename=session.get('filename')
    )

@app.route("/ergot_detected")
def ergot_detected():
    return render_template(
        "ergot_detected.html",
        result=session.get('result'),
        confidence=session.get('confidence'),
        filename=session.get('filename'),
        severity=session.get('severity'),
        risk=session.get('risk')
    )

# ---------------------- PREDICTION LOGIC ----------------------

@app.route("/predict", methods=["POST"])
def predict():
    if "file" not in request.files:
        return jsonify({"error": "No file uploaded"})

    file = request.files["file"]
    upload_dir = os.path.join(app.static_folder, "uploads")
    os.makedirs(upload_dir, exist_ok=True)
    file_path = os.path.join(upload_dir, file.filename)
    file.save(file_path)



    img = preprocess_image(file_path)
    pred = model.predict(img)[0][0]


    
    confidence = round(float(pred) * 100, 2)

    session['filename'] = file.filename
    session['confidence'] = confidence

    severity = get_severity(confidence)
    risk = get_risk(severity)

    session['severity'] = severity
    session['risk'] = risk

    if pred > 0.5:
        session['result'] = 'Healthy'
        return redirect(url_for('results_healthy'))
    else:
        session['result'] = 'Diseased: Ergot'
        return redirect(url_for('ergot_detected'))

# ---------------------- RUN APP ----------------------

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