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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+deepfake/test.jpg filter=lfs diff=lfs merge=lfs -text

deepfake/app.py

@@ -0,0 +1,32 @@
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
+import torch
+
+model_name = "dima806/deepfake_vs_real_image_detection"
+
+# Load processor + model
+processor = AutoImageProcessor.from_pretrained(model_name)
+model = AutoModelForImageClassification.from_pretrained(model_name)
+
+model.eval()
+
+# Test with sample image
+image = Image.open("test.jpg").convert("RGB")
+
+inputs = processor(images=image, return_tensors="pt")
+
+with torch.no_grad():
+    outputs = model(**inputs)
+
+logits = outputs.logits
+probs = torch.softmax(logits, dim=1)
+
+print("Probabilities:", probs)
+print("Predicted class:", probs.argmax().item())
+
+print(model.config.id2label)
+
+fake_index = 1  # confirm from id2label
+deepfake_prob = probs[0][fake_index].item()
+
+print("Deepfake Probability:", deepfake_prob)