Upload folder using huggingface_hub

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml

.idea/backend.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.8 (predict sales-20240912T033332Z-001)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (predict sales-20240912T033332Z-001)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/backend.iml" filepath="$PROJECT_DIR$/.idea/backend.iml" />
+    </modules>
+  </component>
+</project>

.idea/workspace.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ChangeListManager">
+    <list default="true" id="853fda89-837b-4955-a3c2-fb7c30d78d57" name="Changes" comment="" />
+    <option name="SHOW_DIALOG" value="false" />
+    <option name="HIGHLIGHT_CONFLICTS" value="true" />
+    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
+    <option name="LAST_RESOLUTION" value="IGNORE" />
+  </component>
+  <component name="FileTemplateManagerImpl">
+    <option name="RECENT_TEMPLATES">
+      <list>
+        <option value="Python Script" />
+      </list>
+    </option>
+  </component>
+  <component name="ProjectColorInfo"><![CDATA[{
+  "associatedIndex": 4
+}]]></component>
+  <component name="ProjectId" id="2xXey8EmVFqrSUWnQ8gkJgeV09q" />
+  <component name="ProjectViewState">
+    <option name="autoscrollToSource" value="true" />
+    <option name="hideEmptyMiddlePackages" value="true" />
+    <option name="showLibraryContents" value="true" />
+  </component>
+  <component name="PropertiesComponent"><![CDATA[{
+  "keyToString": {
+    "RunOnceActivity.OpenProjectViewOnStart": "true",
+    "RunOnceActivity.ShowReadmeOnStart": "true",
+    "last_opened_file_path": "C:/Users/PMLS/Desktop/backend"
+  }
+}]]></component>
+  <component name="SharedIndexes">
+    <attachedChunks>
+      <set>
+        <option value="bundled-python-sdk-67fca87a943a-d3b881c8e49f-com.jetbrains.pycharm.community.sharedIndexes.bundled-PC-233.11799.259" />
+      </set>
+    </attachedChunks>
+  </component>
+  <component name="SpellCheckerSettings" RuntimeDictionaries="0" Folders="0" CustomDictionaries="0" DefaultDictionary="application-level" UseSingleDictionary="true" transferred="true" />
+  <component name="TaskManager">
+    <task active="true" id="Default" summary="Default task">
+      <changelist id="853fda89-837b-4955-a3c2-fb7c30d78d57" name="Changes" comment="" />
+      <created>1748089096862</created>
+      <option name="number" value="Default" />
+      <option name="presentableId" value="Default" />
+      <updated>1748089096862</updated>
+    </task>
+    <servers />
+  </component>
+</project>

app.py

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+from flask import Flask, request, jsonify, render_template, url_for
+from flask_cors import CORS  # Import CORS
+import torch
+import torch.nn as nn
+from torchvision import models, transforms
+from PIL import Image
+from huggingface_hub import hf_hub_download  # Make sure this import is included
+import os
+from mtcnn import MTCNN  
+import cv2
+from flask_bcrypt import generate_password_hash, check_password_hash
+from flask_cors import CORS
+from pymongo import MongoClient
+import numpy as np
+from flask import Flask, request, jsonify
+from werkzeug.security import generate_password_hash, check_password_hash
+from pymongo import MongoClient
+import logging
+from flask import Flask, request, jsonify, url_for
+from flask_cors import CORS
+from werkzeug.utils import secure_filename
+import os
+from PIL import Image
+import matplotlib.pyplot as plt
+import numpy as np
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+
+# Setup logging
+logging.basicConfig(level=logging.INFO)
+
+
+app = Flask(__name__, template_folder="templates", static_folder="static")
+CORS(app)  # Enable CORS for the Flask app
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+UPLOAD_FOLDER = "static/uploads"
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+
+# Load Model Function
+def load_model_from_hf(repo_id, filename, num_classes):
+    model_path = hf_hub_download(repo_id=repo_id, filename=filename)
+    model = models.convnext_tiny(weights=None)
+    in_features = model.classifier[2].in_features
+    model.classifier[2] = nn.Linear(in_features, num_classes)
+    model.load_state_dict(torch.load(model_path, map_location=device))
+    model.to(device)
+    model.eval()
+    return model
+
+# Load Models
+deepfake_model = load_model_from_hf("faryalnimra/DFDC-detection-model", "DFDC.pth", 2)  
+cheapfake_model = load_model_from_hf("faryalnimra/ORIG-TAMP", "ORIG-TAMP.pth", 1)
+realfake_model = load_model_from_hf("faryalnimra/RealFake", "real_fake.pth", 1)  # New model added (only loaded, not used)
+
+# Image Preprocessing
+transform = transforms.Compose([
+    transforms.ToTensor(),
+    transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+])
+
+face_detector = MTCNN()
+
+def detect_face(image_path):
+    image = cv2.imread(image_path)
+    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    faces = face_detector.detect_faces(image_rgb)
+    face_count = sum(1 for face in faces if face.get("confidence", 0) > 0.90 and face.get("box", [0, 0, 0, 0])[2] > 30)
+    return face_count
+
+@app.route("/predict", methods=["POST"])
+def predict():
+    if "file" not in request.files:
+        return jsonify({"error": "No file uploaded"}), 400
+    
+    file = request.files["file"]
+    filename = os.path.join(UPLOAD_FOLDER, file.filename)
+    file.save(filename)
+
+    try:
+        image = Image.open(filename).convert("RGB")
+        image_tensor = transform(image).unsqueeze(0).to(device)
+    except Exception as e:
+        return jsonify({"error": "Error processing image", "details": str(e)}), 500
+
+    with torch.no_grad():
+        deepfake_probs = torch.softmax(deepfake_model(image_tensor), dim=1)[0]
+        deepfake_confidence_before = deepfake_probs[1].item() * 100  
+        cheapfake_confidence_before = torch.sigmoid(cheapfake_model(image_tensor)).item() * 100  
+
+    face_count = detect_face(filename)
+    face_factor = min(face_count / 2, 1)  
+
+    if deepfake_confidence_before <= cheapfake_confidence_before:
+        adjusted_deepfake_confidence = deepfake_confidence_before * (1 + 0.3 * face_factor)
+        adjusted_cheapfake_confidence = cheapfake_confidence_before * (1 - 0.3 * face_factor)
+    else:
+        adjusted_deepfake_confidence = deepfake_confidence_before
+        adjusted_cheapfake_confidence = cheapfake_confidence_before
+
+    fake_type = "Deepfake" if adjusted_deepfake_confidence > adjusted_cheapfake_confidence else "Cheapfake"
+    # Print the result to the terminal
+    print(f"Prediction: Fake")
+    print(f"Fake Type: {fake_type}")
+    print(f"Deepfake Confidence Before: {deepfake_confidence_before:.2f}%")
+    print(f"Deepfake Confidence Adjusted: {adjusted_deepfake_confidence:.2f}%")
+    print(f"Cheapfake Confidence Before: {cheapfake_confidence_before:.2f}%")
+    print(f"Cheapfake Confidence Adjusted: {adjusted_cheapfake_confidence:.2f}%")
+    print(f"Faces Detected: {face_count}")
+    print(f"Image URL: {url_for('static', filename=f'uploads/{file.filename}')}")
+
+    return jsonify({
+        "prediction": "Fake",
+        "fake_type": fake_type,
+        "deepfake_confidence_before": f"{deepfake_confidence_before:.2f}%",
+        "deepfake_confidence_adjusted": f"{adjusted_deepfake_confidence:.2f}%",
+        "cheapfake_confidence_before": f"{cheapfake_confidence_before:.2f}%",
+        "cheapfake_confidence_adjusted": f"{adjusted_cheapfake_confidence:.2f}%",
+        "faces_detected": face_count,
+        "image_url": url_for("static", filename=f"uploads/{file.filename}")
+    })
+
+HEATMAP_FOLDER = "static/heatmaps"
+os.makedirs(HEATMAP_FOLDER, exist_ok=True)
+
+
+ALLOWED_EXTENSIONS = {"png", "jpg", "jpeg"}  # Allow these extensions
+UPLOAD_FOLDER = "static/uploads"
+HEATMAP_FOLDER = "static/heatmaps"
+
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+os.makedirs(HEATMAP_FOLDER, exist_ok=True)
+
+# Check if the uploaded file has an allowed extension
+def allowed_file(filename):
+    return "." in filename and filename.rsplit(".", 1)[1].lower() in ALLOWED_EXTENSIONS
+
+# ✨ Heatmap generator (Grid based)
+def generate_heatmap(original_image_path, heatmap_save_path):
+    try:
+        print(f"Opening image: {original_image_path}")  # Debug print
+        img = Image.open(original_image_path).convert("L")  # Convert to Grayscale
+        print(f"Image opened successfully: {original_image_path}")  # Debug print
+        
+        img = img.resize((20, 20))  # Resize to small grid (adjust as needed)
+        print(f"Image resized to: {img.size}")  # Debug print
+
+        img_array = np.array(img)
+
+        plt.figure(figsize=(10, 8))
+        sns.heatmap(img_array, cmap="coolwarm", cbar=True, square=True, linewidths=0.5)
+
+        plt.axis('off')  # Hide axis if you want
+        plt.savefig(heatmap_save_path, bbox_inches='tight', pad_inches=0)
+        plt.close()
+        print(f"Heatmap saved to: {heatmap_save_path}")  # Debug print
+    except Exception as e:
+        print(f"Heatmap generation failed for {original_image_path}: {e}")  # Print specific error
+
+@app.route("/generate_heatmap", methods=["POST"])
+def generate_heatmap_api():
+    if "file" not in request.files:
+        return jsonify({"error": "No file uploaded"}), 400
+
+    file = request.files["file"]
+    
+    if file.filename == "" or not allowed_file(file.filename):
+        return jsonify({"error": "Invalid file type. Allowed types are .png, .jpg, .jpeg, .tif, .tiff"}), 400
+
+    filename = secure_filename(file.filename)
+    original_image_path = os.path.join(UPLOAD_FOLDER, filename)
+    
+    try:
+        file.save(original_image_path)
+        print(f"File saved to: {original_image_path}")  # Debug print
+    except Exception as e:
+        print(f"Error saving file: {e}")
+        return jsonify({"error": "Failed to save the file"}), 500
+
+    heatmap_filename = f"heatmap_{filename}"
+    heatmap_path = os.path.join(HEATMAP_FOLDER, heatmap_filename)
+    
+    generate_heatmap(original_image_path, heatmap_path)
+
+    return jsonify({
+        "original_image_url": url_for("static", filename=f"uploads/{filename}", _external=True),
+        "heatmap_image_url": url_for("static", filename=f"heatmaps/{heatmap_filename}", _external=True)
+    })
+
+
+#MongoDB Atlantis from flask import Flask, request, jsonify
+
+
+# MongoDB connection
+client = MongoClient('mongodb+srv://fakecatcherai:sX_W9!SUigNS.ww@cluster0.pwyazjb.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0')
+db = client['fakecatcherDB']
+users_collection = db['users']
+contacts_collection = db['contacts']
+
+def is_valid_password(password):
+    if (len(password) < 8 or
+        not re.search(r'[A-Z]', password) or
+        not re.search(r'[a-z]', password) or
+        not re.search(r'[0-9]', password) or
+        not re.search(r'[!@#$%^&*(),.?":{}|<>]', password)):
+        return False
+    return True
+
+@app.route('/Register', methods=['POST'])
+def register():
+    data = request.get_json()
+    first_name = data.get('firstName')
+    last_name = data.get('lastName')
+    email = data.get('email')
+    password = data.get('password')
+
+    if users_collection.find_one({'email': email}):
+        logging.warning(f"Attempted register with existing email: {email}")
+        return jsonify({'message': 'Email already exists!'}), 400
+
+    # ✅ Password constraints check
+    if not is_valid_password(password):
+        return jsonify({'message': 'Password must be at least 8 characters long and include uppercase, lowercase, number, and special character.'}), 400
+
+    hashed_pw = generate_password_hash(password)
+    users_collection.insert_one({
+        'first_name': first_name,
+        'last_name': last_name,
+        'email': email,
+        'password': hashed_pw
+    })
+
+    logging.info(f"New user registered: {first_name} {last_name}, Email: {email}")
+    return jsonify({'message': 'Registration successful!'}), 201
+
+# 🔵 Login Route
+@app.route('/Login', methods=['POST'])
+def login():
+    data = request.get_json()
+    email = data.get('email')
+    password = data.get('password')
+
+    # Check if the user exists
+    user = users_collection.find_one({'email': email})
+    if not user or not check_password_hash(user['password'], password):
+        logging.warning(f"Failed login attempt for email: {email}")
+        return jsonify({'message': 'Invalid email or password!'}), 401
+
+    logging.info(f"User logged in successfully: {email}")
+    return jsonify({'message': 'Login successful!'}), 200
+@app.route('/ForgotPassword', methods=['POST'])
+def forgot_password():
+    data = request.get_json()
+    email = data.get('email')
+    new_password = data.get('newPassword')
+    confirm_password = data.get('confirmPassword')
+
+    # Check if passwords match
+    if new_password != confirm_password:
+        logging.warning(f"Password reset failed. Passwords do not match for email: {email}")
+        return jsonify({'message': 'Passwords do not match!'}), 400
+
+    # Check if the user exists
+    user = users_collection.find_one({'email': email})
+    if not user:
+        logging.warning(f"Password reset attempt for non-existent email: {email}")
+        return jsonify({'message': 'User not found!'}), 404
+
+    # Hash the new password and update it
+    hashed_pw = generate_password_hash(new_password)
+    users_collection.update_one({'email': email}, {'$set': {'password': hashed_pw}})
+
+    logging.info(f"Password successfully reset for email: {email}")
+    return jsonify({'message': 'Password updated successfully!'}), 200
+
+
+
+
+   
+
+# 🟣 Contact Form Route (React Page: Contact)
+@app.route('/Contact', methods=['POST'])
+def contact():
+    data = request.get_json()
+    email = data.get('email')
+    query = data.get('query')
+    message = data.get('message')
+
+    # Check if all fields are provided
+    if not email or not query or not message:
+        logging.warning(f"Incomplete contact form submission from email: {email}")
+        return jsonify({'message': 'All fields are required!'}), 400
+
+    # Insert the contact data
+    contact_data = {
+        'email': email,
+        'query': query,
+        'message': message
+    }
+    contacts_collection.insert_one(contact_data)
+
+    logging.info(f"Contact form submitted successfully from email: {email}")
+    return jsonify({'message': 'Your message has been sent successfully.'}), 200
+
+if __name__ == '__main__':
+    app.run(debug=True)

requirements.txt

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+# Deep learning
+torch==2.2.2
+torchvision
+facenet-pytorch
+
+# Flask & Web
+Flask
+Flask-Bcrypt
+Flask-Cors
+Werkzeug
+Jinja2
+itsdangerous
+
+# Image, ML, and Data
+opencv-python
+opencv-contrib-python
+pillow
+numpy
+scikit-learn
+pandas
+matplotlib
+seaborn
+mediapipe
+mtcnn
+retina-face
+transformers
+huggingface-hub
+gdown
+
+# Utility & Auth
+requests
+requests-oauthlib
+google-auth
+google-auth-oauthlib
+PyQt5
+fpdf
+bcrypt
+dnspython
+pymongo
+
+# Logging & Plotting
+tensorboard
+
+# Environment
+virtualenv
+gunicorn

test.py

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+from huggingface_hub import HfApi
+
+api = HfApi()
+
+api.upload_folder(
+    folder_path=r"C:\Users\PMLS\Desktop\backend",
+    repo_id="faryalnimra/backend",
+    repo_type="space"
+)