Update app.py

app.py

@@ -1,15 +1,28 @@
 import gradio as gr
 import AAMD
+from pyAAMED import pyAAMED
+import cv2
 
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+title = """
+<h1>Arc Adjacency Matrix based Fast Ellipse Detection</h1>
+<a href="https://github.com/Li-Zhaoxi/AAMED">Gitub</a>
+"""
 
-def predict(image):
-    predictions = pipeline(image)
-    return {p["label"]: p["score"] for p in predictions}
+def detect_ellipses(img_path):
+    imgC = cv2.imread(img_path)
+    imgG = cv2.cvtColor(imgC, cv2.COLOR_BGR2GRAY)
+
+    aamed = pyAAMED(600, 600)
+
+    aamed.setParameters(3.1415926/3, 3.4, 0.77)
+    res = aamed.run_AAMED(imgG)
+    print(res)
+
+    return img
 
 gr.Interface(
-    predict,
-    inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
-    outputs=gr.outputs.Label(num_top_classes=2),
-    title="Hot Dog? Or Not?",
+    detect_ellipses,
+    inputs=gr.inputs.Image(label="Upload image with ellipses", type="filepath"),
+    outputs=gr.outputs.Image(label="Detected ellipses"),
+    title=title,
 ).launch()