Update app.py

app.py

@@ -24,37 +24,42 @@ for img in source_imgs:
   try:
     faces, id = extract_faces(detector, img)
     source_faces.append(faces[id])
-    source_faces.append(Image.open(img))
+    # source_faces.append(Image.open(img))
   except Exception as e:
     print(f"Skipping {img}, {e}")
 
 source_embeddings = get_embeddings(model, source_faces)
 
-def find_names(image):
+def find_names(image, minSize, minConf):
   imgs, _ = extract_faces(detector, image)
   for i, face in enumerate(imgs):
-    if(face.size[0] * face.size[1] < 1000):
+    print(face.size[0], face.size[1])
+    if(face.size[0] * face.size[1] < minSize):
       del imgs[i]
 
   embeds = get_embeddings(model, imgs)
+  print(len(embeds))
   d = np.zeros((len(source_embeddings), len(embeds)))
   for i, s in enumerate(source_embeddings):
     for j, t in enumerate(embeds):
       d[i][j] = findCosineDistance(s, t)
   ids = np.argmin(d, axis = 0)
   names = []
-  for i in ids:
-    names.append(source_imgs[i].split("/")[-1].split(".")[0])
+  for j, i in enumerate(ids):
+    if 1 - d[i][j] > minConf:
+        names.append(source_imgs[i].split("/")[-1].split(".")[0])
+    else:
+        names.append("Unknown")
   recognition(imgs, ids, names, source_faces, d, source_imgs)
   return ",".join(names), "Recognition.jpg"
 
 detect = gr.Interface(
     find_names,
-    gr.Image(type="filepath"),
-    ["text", gr.Image(type = "filepath")],
+    [gr.Image(type="filepath", label="Class Photo"), gr.Number(label = "Minimum Size"), gr.Number(label = "Minimum Confidence")],
+    ["text" ,gr.Image(type = "filepath", label="Matching")],
     examples = [
-        os.path.join(os.path.dirname(__file__), "examples/group1.jpg"),
-        os.path.join(os.path.dirname(__file__), "examples/group2.jpg")
+        [os.path.join(os.path.dirname(__file__), "examples/group1.jpg"), 1000, 0.3],
+        [os.path.join(os.path.dirname(__file__), "examples/group2.jpg"), 1000, 0.3]
     ]
 )
 
@@ -106,8 +111,9 @@ i = 0
 imgs = None
 
 with gr.Blocks() as annotate:
-    output = gr.Image(type="pil", label="Image")
-    input = gr.Textbox(label = "Enter Label")
+    with gr.Row():
+        input = gr.Textbox(label = "Enter Label")
+        output = gr.Image(type="pil", label="Image").style(height=400)
     with gr.Row():
         next_btn = gr.Button(value="Next")
         next_btn.click(load_image, inputs=[], outputs=[output, input])