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README.md

@@ -1,12 +1,6 @@
 ---
 title: RealVFake
-emoji: 🔥
-colorFrom: purple
-colorTo: indigo
-sdk: gradio
-sdk_version: 4.19.2
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 3.44.4
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import tensorflow as tf
+from tensorflow.keras.models import load_model
+from PIL import Image
+import requests
+from io import BytesIO
+from matplotlib import pyplot as plt
+import numpy as np
+import gradio as gr
+import json
+
+model = load_model('real-fake-best.h5')
+
+def index(image_url):
+    response = requests.get(image_url)
+    img = Image.open(BytesIO(response.content))
+    img = np.array(img)  
+
+    resize = tf.image.resize(img, (32, 32))
+
+    y_pred = model.predict(np.expand_dims(resize / 255, 0))
+
+    predictions = {"Fake": y_pred[0][0]*100, "Real": y_pred[0][1]*100}
+
+    print("Predictions:", y_pred)
+    predicted_class = np.argmax(y_pred)
+    print("Predicted Class:", predicted_class)
+
+    return json.dumps(predictions)
+
+inputs_image_url = [
+    gr.Textbox(type="text", label="Image URL"),
+]
+
+outputs_result_dict = [
+    gr.Textbox(type="text", label="Result Dictionary"),
+]
+
+interface_image_url = gr.Interface(
+    fn=index,
+    inputs=inputs_image_url,
+    outputs=outputs_result_dict,
+    title="AI Image Detection",
+    cache_examples=False,
+)
+
+gr.TabbedInterface(
+    [interface_image_url],
+    tab_names=['Image inference']
+).queue().launch()
+
+
+# 0 -> AI
+# 1 -> Real
+
+# if y_pred > 0.5:
+#     print(f'REAL')
+# else:
+#     print(f'AI')

real-fake-best.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:35ccc9c462511d4254e0ba3ac535c24d0079b06c618b0d34b0738d6cda86bcea
+size 521584

requirements.txt

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+tensorflow
+opencv-python
+matplotlib
+numpy
+gradio