Refactor inference function in app.py to accept image file path, update output to include file path, and adjust input type in the UI.

app.py

@@ -20,7 +20,7 @@ from utils import (
 from flagging import HuggingFaceDatasetSaver
 
 import install_private_repos  # noqa: F401
-from seavision import load_model
+from seavision import load_model, imread
 
 
 TITLE = """
@@ -53,10 +53,11 @@ model.hor_conf_thresh = 0.1
 
 
 # @spaces.GPU
-def inference(image):
+def inference(image_fp):
     """Run inference on image and return annotated image."""
+    image = imread(image_fp)
     results = model(image)
-    return results.draw(image)
+    return results.draw(image), image_fp
 
 
 def flag_img_input(
@@ -64,7 +65,7 @@ def flag_img_input(
 ):
     """Wrapper for flagging"""
     print(f"{image=}, {flag_option=}, {username=}")
-    return hf_writer.flag([image], flag_option=flag_option, username=username)
+    hf_writer.flag([image], flag_option=flag_option, username=username)
 
 
 # Flagging
@@ -84,7 +85,7 @@ with gr.Blocks(theme=theme, css=css, title="SEA.AI Vision Demo") as demo:
                 label="input",
                 interactive=True,
                 sources=["upload", "clipboard"],
-                type="numpy",
+                type="filepath",
             )
             img_url = gr.Textbox(
                 lines=1,
@@ -97,13 +98,14 @@ with gr.Blocks(theme=theme, css=css, title="SEA.AI Vision Demo") as demo:
                 submit = gr.Button("Submit", variant="primary")
         with gr.Column():
             img_output = gr.Image(label="output", interactive=False)
+            img_filepath = gr.Textbox(label="image_fp", visible=False)
             flag = gr.Button(FLAG_TXT, visible=False)
             notice = gr.Markdown(value=NOTICE, visible=False)
 
     examples = gr.Examples(
         examples=glob.glob("examples/*.jpg"),
         inputs=img_input,
-        outputs=img_output,
+        outputs=[img_output, img_filepath],
         fn=inference,
         cache_examples=True,
     )
@@ -116,7 +118,7 @@ with gr.Blocks(theme=theme, css=css, title="SEA.AI Vision Demo") as demo:
     submit.click(check_image, [img_input], None, show_api=False).success(
         inference,
         [img_input],
-        img_output,
+        [img_output, img_filepath],
         api_name="inference",
     )