added examples from own DB

app.py

@@ -1,3 +1,4 @@
+import glob
 import gradio as gr
 from huggingface_hub import get_token
 from utils import load_model, load_image_from_url, inference, load_badges
@@ -27,7 +28,7 @@ h1 {
 """
 
 model = load_model("SEA-AI/yolov5n6-RGB", img_size=1280)
-model.conf = 0.25
+model.conf = 0.2
 model.iou = 0.4
 model.max_det = 100
 model.agnostic = True  # NMS class-agnostic
@@ -60,11 +61,7 @@ with gr.Blocks(css=css) as demo:
             notice = gr.Markdown(value=NOTICE, visible=False)
 
     gr.Examples(
-        examples=[
-            "https://images.pexels.com/photos/273886/pexels-photo-273886.jpeg?auto=compress&cs=tinysrgb&w=1260&h=750&dpr=2",
-            "https://images.pexels.com/photos/913111/pexels-photo-913111.jpeg?auto=compress&cs=tinysrgb&w=1260&h=750&dpr=2",
-            "https://images.pexels.com/photos/88517/pexels-photo-88517.jpeg?auto=compress&cs=tinysrgb&w=1260&h=750&dpr=2",
-        ],
+        examples=glob.glob("examples/*.jpg"),
         inputs=img_input,
         outputs=img_output,
         fn=lambda image: inference(model, image),
@@ -83,21 +80,24 @@ with gr.Blocks(css=css) as demo:
     def show_hide(img_output):
         visible = img_output is not None
         return {
-            flag: gr.Button("Flag", visible=visible),
+            flag: gr.Button("Flag", visible=visible, interactive=True),
             notice: gr.Markdown(value=NOTICE, visible=visible),
         }
 
     # This needs to be called prior to the first call to callback.flag()
     hf_writer.setup([img_input], "flagged")
-    img_input.flag
 
     # We can choose which components to flag (in this case, we'll flag all)
     flag.click(lambda: gr.Info("Thank you for contributing!")).then(
+        lambda: {flag: gr.Button("Flag", interactive=False)}, [], [flag]
+    ).then(
         lambda *args: hf_writer.flag(args),
         [img_input, flag],
         [],
         preprocess=False,
-    ).then(lambda: load_badges(dataset_name), [], badges)
+    ).then(
+        lambda: load_badges(dataset_name), [], badges
+    )
 
 if __name__ == "__main__":
     demo.queue().launch()