| import gradio as gr |
| import torch |
| from PIL import Image |
| from transformers import ViTForImageClassification, ViTImageProcessor, CLIPProcessor, CLIPModel |
|
|
| """Load models""" |
| |
| deepfake_model = ViTForImageClassification.from_pretrained("prithivMLmods/Deep-Fake-Detector-v2-Model") |
| deepfake_processor = ViTImageProcessor.from_pretrained("prithivMLmods/Deep-Fake-Detector-v2-Model") |
| clip_model_path = "openai/clip-vit-base-patch32" |
|
|
| clip_model = CLIPModel.from_pretrained(clip_model_path) |
| clip_processor = CLIPProcessor.from_pretrained(clip_model_path) |
| clip_model.eval() |
| deepfake_model.eval() |
|
|
| clip_labels = ["photo of a real person or scene", "synthetic or AI generated image"] |
|
|
|
|
| def hybrid_classifier(img: Image.Image): |
| df_inputs = deepfake_processor(images=img, return_tensors="pt") |
| with torch.no_grad(): |
| df_outputs = deepfake_model(**df_inputs) |
| df_probs = torch.nn.functional.softmax(df_outputs.logits, dim=1) |
| df_real_score = df_probs[0][deepfake_model.config.label2id["Realism"]].item() |
| df_fake_score = df_probs[0][deepfake_model.config.label2id["Deepfake"]].item() |
|
|
| clip_inputs = clip_processor(text=clip_labels, images=img, return_tensors="pt", padding=True) |
| with torch.no_grad(): |
| clip_outputs = clip_model(**clip_inputs) |
| clip_probs = torch.softmax(clip_outputs.logits_per_image, dim=1).squeeze() |
| clip_real_score = clip_probs[0].item() |
| clip_fake_score = clip_probs[1].item() |
|
|
| final_real_score = (0.3 * df_real_score + 0.7 * clip_real_score) |
| final_fake_score = (0.3 * df_fake_score + 0.7 * clip_fake_score) |
|
|
| decision = "Generated" |
| if abs(final_real_score - final_fake_score) > 0.3: |
| decision = "Real" if final_real_score > final_fake_score else decision |
|
|
| return decision |
|
|
|
|
| """Preset and launch Gradio """ |
| iface = gr.Interface( |
| fn=hybrid_classifier, |
| inputs=gr.Image(type="pil"), |
| outputs=gr.Textbox(label="Final Decision"), |
| title="RealifyAI", |
| description="Figure out if image real or generated", |
| examples=[["https://huggingface.co/spaces/alfakat/RealifyAI/resolve/main/examples/image00.jpg"], |
| ["https://huggingface.co/spaces/alfakat/RealifyAI/resolve/main/examples/image01.jpg"], |
| ["https://huggingface.co/spaces/alfakat/RealifyAI/resolve/main/examples/image02.jpg"]]) |
|
|
| if __name__ == "__main__": |
| iface.launch() |
|
|
