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.gitignore

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+examples/

README.md

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 ---
-title: Detection With Explanations
-emoji: 📈
-colorFrom: green
-colorTo: gray
+title: Deepfake Detection
+emoji: 📚
+colorFrom: red
+colorTo: indigo
 sdk: gradio
-sdk_version: 4.16.0
+sdk_version: 3.0.14
 app_file: app.py
 pinned: false
-license: mit
+license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import torch
+import torch.nn.functional as F
+from facenet_pytorch import MTCNN, InceptionResnetV1
+import os
+import numpy as np
+from PIL import Image
+import zipfile
+import cv2
+from pytorch_grad_cam import GradCAM
+from pytorch_grad_cam.utils.model_targets import ClassifierOutputTarget
+from pytorch_grad_cam.utils.image import show_cam_on_image
+from transformers import pipeline
+with zipfile.ZipFile("examples.zip","r") as zip_ref:
+    zip_ref.extractall(".")
+
+pipe = pipeline(model="SivaResearch/Fake_Detection",trust_remote_code=True)
+
+EXAMPLES_FOLDER = 'examples'
+examples_names = os.listdir(EXAMPLES_FOLDER)
+examples = []
+for example_name in examples_names:
+    example_path = os.path.join(EXAMPLES_FOLDER, example_name)
+    label = example_name.split('_')[0]
+    example = {
+        'path': example_path,
+        'label': label
+    }
+    examples.append(example)
+np.random.shuffle(examples) # shuffle
+
+def predict(input_image:Image.Image, true_label:str):
+    out = pipe.predict(input_image)
+    confidences,face_with_mask = out["confidences"], out["face_with_mask"]
+    return confidences, true_label, face_with_mask
+
+interface = gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.Image(label="Input Image", type="filepath"),
+        "text"
+    ],
+    outputs=[
+        gr.Label(label="Class"),
+        "text",
+        gr.Image(label="Face with Explainability")
+    ],
+    examples=[[examples[i]["path"], examples[i]["label"]] for i in range(10)]
+).launch()

examples.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9c719c2f16bad2e71d0d33d6ae59fa646dac82a812e1a90578c4b97ef6e8f36c
+size 28750945

requirements.txt

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+gradio
+Pillow
+facenet-pytorch
+torch
+opencv-python
+grad-cam
+transformers