Update app.py

app.py

@@ -6,12 +6,12 @@ import os
 
 # Sample media paths and thumbnails
 sample_images = {
-    "Unorganized": ("samples/unorganized.jpg", "samples/unorganized_thumb.jpg"),
-    "Organized": ("samples/organized.jpg", "samples/organized_thumb.jpg")
+    "Unorganized": "samples/unorganized.jpg",
+    "Organized": "samples/organized.jpg"
 }
 
 sample_videos = {
-    "Sample Video": ("samples/sample_video.mp4", "samples/sample_video_thumb.jpg")
+    "Sample Video": "samples/sample_video.mp4"
 }
 
 def load_model(model_name):
@@ -27,13 +27,13 @@ models = {
 def detect_image(model_choice, input_image=None, sample_image_choice=None):
     model = load_model(models[model_choice])
     if sample_image_choice:
-        input_image = Image.open(sample_images[sample_image_choice][0])
+        input_image = Image.open(sample_images[sample_image_choice])
     return model.detect_image(input_image)
 
 def detect_video(model_choice, input_video=None, sample_video_choice=None):
     model = load_model(models[model_choice])
     if sample_video_choice:
-        input_video = sample_videos[sample_video_choice][0]
+        input_video = sample_videos[sample_video_choice]
     return model.detect_video(input_video)
 
 app = gr.Blocks()
@@ -42,32 +42,30 @@ with app:
     gr.Markdown("## Object Detection using TensorFlow Lite Models")
     with gr.Row():
         model_choice = gr.Dropdown(label="Select Model", choices=list(models.keys()))
-
+        
         with gr.Tab("Image Detection"):
             with gr.Column():
-                image_input = gr.Image(type="pil", label="Upload an image")
-                gr.Markdown("### Or select a sample image")
-                sample_image_choice = gr.Gallery(choices=list(sample_images.keys()), label="Sample Images")
+                image_input = gr.Image(type="pil", label="Upload an image (or use sample)")
+                sample_image_choice = gr.Dropdown(
+                    label="Or select a sample image",
+                    choices=[None] + list(sample_images.keys()),
+                    value=None
+                )
                 image_output = gr.Image(type="pil", label="Detection Result")
                 gr.Button("Submit Image").click(
                     fn=detect_image, 
                     inputs=[model_choice, image_input, sample_image_choice], 
                     outputs=image_output
                 )
-
+        
         with gr.Tab("Video Detection"):
             with gr.Column():
-                video_input = gr.Video(label="Upload a video")
-                gr.Markdown("### Or select a sample video")
+                video_input = gr.Video(label="Upload a video (or use sample)")
                 sample_video_choice = gr.Dropdown(
-                    label="Sample Videos",
-                    choices=list(sample_videos.keys()),
+                    label="Or select a sample video",
+                    choices=[None] + list(sample_videos.keys()),
                     value=None
                 )
-                video_thumbnails = gr.HTML(value="<div>" + "".join([
-                    f'<div style="display:inline-block; padding:10px;"><img src="{sample_videos[video][1]}" style="width:150px; cursor:pointer;" onclick="document.querySelector(\'select[name=sample_video_choice]\').value=\'{video}\';"></div>'
-                    for video in sample_videos
-                ]) + "</div>")
                 video_output = gr.Video(label="Detection Result")
                 gr.Button("Submit Video").click(
                     fn=detect_video,