Refactor flagging mechanism in app.py to use dedicated function for image flagging and clean up commented code.

app.py

@@ -7,7 +7,7 @@ Any new model should implement the following functions:
 
 import os
 import glob
-import spaces
+#import spaces
 import gradio as gr
 from huggingface_hub import get_token
 from utils import (
@@ -50,12 +50,16 @@ model = load_model("experimental/ahoy6-MIX-1280-b1.onnx")
 model.det_conf_thresh = 0.1
 model.hor_conf_thresh = 0.1
 
-@spaces.GPU
+# @spaces.GPU
 def inference(image):
     """Run inference on image and return annotated image."""
     results = model(image)
     return results.draw(image)
 
+def flag_img_input(image: gr.Image, flag_option: str = "misdetection", username: str = "anonymous"):
+    """Wrapper for flagging"""
+    return hf_writer.flag([image], flag_option=flag_option, username=username)
+
 # Flagging
 dataset_name = "SEA-AI/crowdsourced-sea-images"
 hf_writer = HuggingFaceDatasetSaver(get_token(), dataset_name)
@@ -131,14 +135,14 @@ with gr.Blocks(theme=theme, css=css, title="SEA.AI Vision Demo") as demo:
         [flag],
         show_api=False,
     ).then(
-        lambda img_input, flag: hf_writer.flag(img_input, flag),
-        [img_input, flag],
+        flag_img_input,
+        [img_input],
         [],
         preprocess=False,
         show_api=True,
         api_name="flag_misdetection"
     ).then(
-        lambda: load_badges(flagged_counter.count()), [], badges, show_api=False
+        lambda: load_badges(flagged_counter.count()), [], badges, show_api=False,
     )
 
     # called during initial load in browser