Remove deprecated image detection module

backend/app/image_detection/detector.py

@@ -1,35 +0,0 @@
-from PIL import Image
-
-from backend.app.image_detection.univfd_detector import UnivFDDetector
-
-
-class ImageDetector:
-
-    def __init__(self):
-
-        print("Image Detector Initialized")
-
-        self.univfd = UnivFDDetector()
-
-    def predict(self, image_path):
-
-        image = Image.open(image_path)
-
-        width, height = image.size
-        image_format = image.format
-
-        probability = self.univfd.predict(image_path)
-
-        classification = (
-            "AI Generated"
-            if probability > 0.5
-            else "Human Generated"
-        )
-
-        return {
-            "classification": classification,
-            "ai_probability": round(probability * 100, 2),
-            "width": width,
-            "height": height,
-            "format": image_format
-        }

backend/app/image_detection/test_detector.py

@@ -1,14 +0,0 @@
-from pathlib import Path
-from detector import ImageDetector
-
-detector = ImageDetector()
-
-image_path = (
-    Path(__file__).parent
-    / "test_images"
-    / "cat.jpeg"
-)
-
-result = detector.predict(str(image_path))
-
-print(result)

backend/app/image_detection/test_univfd.py

@@ -1,9 +0,0 @@
-from univfd_detector import UnivFDDetector
-
-detector = UnivFDDetector()
-
-result = detector.predict(
-    "backend/app/image_detection/test_images/cat.jpeg"
-)
-
-print(result)

backend/app/image_detection/univfd_detector.py

@@ -1,60 +0,0 @@
-import torch
-from PIL import Image
-from torchvision import transforms
-import sys
-
-# Add UnivFD repo to path
-sys.path.append(
-    r"D:\Projects\AI-claim-verifier\UniversalFakeDetect\UniversalFakeDetect"
-)
-
-from models.imagenet_models import ImagenetModel
-from models.clip_models import CLIPModel
-
-
-class UnivFDDetector:
-
-    def __init__(self):
-
-        print("Loading UnivFD...")
-
-
-        self.model = CLIPModel("ViT-L/14")
-
-        state_dict = torch.load(
-            r"D:\Projects\AI-claim-verifier\UniversalFakeDetect\UniversalFakeDetect\pretrained_weights\fc_weights.pth",
-            map_location="cpu"
-        )
-
-        self.model.fc.load_state_dict(state_dict)
-
-        self.model.eval()
-
-        self.transform = transforms.Compose([
-            transforms.CenterCrop(224),
-            transforms.ToTensor(),
-            transforms.Normalize(
-                mean=[0.485, 0.456, 0.406],
-                std=[0.229, 0.224, 0.225]
-            ),
-        ])
-
-        print("Model Loaded")
-
-    def predict(self, image_path):
-
-        image = Image.open(image_path).convert("RGB")
-
-        image = self.transform(image)
-
-        image = image.unsqueeze(0)
-
-        with torch.no_grad():
-
-            output = self.model(image)
-
-            probability = torch.sigmoid(
-                output
-            ).item()
-
-        return probability