Upload CNN transfer artifacts (model + preprocess + config)

README.md

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----
-license: mit
----
+---
+license: apache-2.0
+tags:
+  - image-classification
+  - deepfake-detection
+  - pytorch
+---
+
+# CNN Transfer (DeepFakeDetector)
+
+Binary image classifier for deepfake or AI-generated image detection.
+
+## Label convention (fixed)
+- 0 = real
+- 1 = fake
+
+## Preprocessing
+- Resize to 224x224
+- Normalize with ImageNet mean/std
+
+## Output
+- prob_fake in [0, 1] computed as softmax(logits)[fake]
+- decision threshold: 0.662

config.json

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+{
+  "name": "cnn-transfer",
+  "framework": "pytorch",
+  "arch": "efficientnet_b0",
+  "num_classes": 2,
+  "threshold": 0.662,
+  "labels": {
+    "0": "real",
+    "1": "fake"
+  },
+  "exported_at_utc": "2026-02-16T23:35:43.373902Z",
+  "notes": "CNN transfer baseline for deepfake detection. prob_fake = softmax(logits)[fake]."
+}

label_map.json

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+{
+  "0": "real",
+  "1": "fake"
+}

model.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5671df633967e535bd7f0dc9a2fd5000cd9edd6358da0f7f0188e94580144610
+size 16320083

preprocess.json

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+{
+  "input_size": [
+    224,
+    224
+  ],
+  "resize": {
+    "enabled": true,
+    "size": [
+      224,
+      224
+    ]
+  },
+  "center_crop": {
+    "enabled": false
+  },
+  "normalize": {
+    "mean": [
+      0.485,
+      0.456,
+      0.406
+    ],
+    "std": [
+      0.229,
+      0.224,
+      0.225
+    ]
+  },
+  "notes": "Resize to IM_SIZE x IM_SIZE then normalize with ImageNet mean/std."
+}