Create app.py

app.py

@@ -0,0 +1,115 @@
+import os
+import gradio as gr
+import json
+from gradio_client import Client, handle_file
+
+backend = Client(os.getenv("BACKEND"), hf_token=os.getenv("TOKEN"))
+JS_FUNC1 = os.getenv("JS_FUNC1")
+JS_FUNC2 = os.getenv("JS_FUNC2")
+
+def detect(image):
+    try:
+        file_1 = handle_file(image)
+    except Exception as e:
+        gr.Info("Please upload an image file.")
+        return "", "", "", {}
+
+    result_text = backend.predict(
+        image=handle_file(image),
+        api_name="/detect"
+    )
+
+    result = json.loads(result_text)
+    if result and result["status"] == "ok":
+        overall = result["overall"]
+        aigen = result["aigen"]
+        deepfake = result["deepfake"]
+
+        breakdown = {
+            "GenAI": 99,
+            "Face Manipulation": 99,
+            "Diffusion (Flux)": 99,
+            "StyleGAN": 0,
+        }
+        return overall, aigen, deepfake, breakdown
+    else:
+        raise gr.Error("Error in processing image")
+
+custom_css = """
+.result-card {
+  background: white;
+  border-radius: 20px;
+  padding: 24px;
+  box-shadow: 0 6px 20px rgba(0,0,0,0.1);
+}
+.result-title {
+  font-size: 20px;
+  font-weight: bold;
+  margin-bottom: 12px;
+}
+.progress-container {
+  margin-bottom: 12px;
+}
+.progress-label {
+  font-size: 14px;
+  font-weight: 500;
+}
+.progress-bar {
+  height: 12px;
+  border-radius: 6px;
+  background: #e5e7eb;
+  margin-top: 4px;
+  overflow: hidden;
+}
+.progress-fill {
+  height: 100%;
+  background: linear-gradient(90deg, #ff416c, #ff4b2b);
+}
+"""
+
+MARKDOWN0 = """
+# 🔍 DeepFake Detector
+Upload an image and check if it’s AI-generated or manipulated.
+"""
+MARKDOWN3 = """
+<div align="right"><a href="https://faceonlive.com/face-search-online" target='_blank'>Reverse Face Search</a></div>
+<div align="right"><a href="https://faceonlive.com/reverse-image-search" target='_blank'>Reverse Image Search</a></div>
+"""
+
+def breakdown_ui(breakdown: dict):
+    html = ""
+    for label, val in breakdown.items():
+        html += f"""
+        <div class="progress-container">
+            <div class="progress-label">{label}: {val}%</div>
+            <div class="progress-bar"><div class="progress-fill" style="width:{val}%;"></div></div>
+        </div>
+        """
+    return html
+
+with gr.Blocks(css=custom_css) as demo:
+    gr.Markdown(MARKDOWN0)
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            image = gr.Image(type='filepath', height=360, label="Upload Image")
+            detect_button = gr.Button("🚀 Detect", elem_classes="button-gradient")
+        with gr.Column(scale=2):
+            overall = gr.Label(label="Overall Result")
+            aigen = gr.Label(label="Generative AI Model")
+            deepfake = gr.Label(label="Face Manipulation")
+            breakdown_html = gr.HTML(label="Detection Breakdown")
+
+    gr.Markdown(MARKDOWN3)
+
+    detect_button.click(
+        detect,
+        inputs=image,
+        outputs=[overall, aigen, deepfake, breakdown_html],
+    ).then(
+        breakdown_ui,
+        inputs=[breakdown_html],
+        outputs=breakdown_html
+    )
+
+demo.launch(server_name="0.0.0.0", share=True)