Update app.py

app.py

@@ -2,20 +2,10 @@ import gradio as gr
 from datasets import load_dataset
 from PIL import Image, ImageDraw
 import numpy as np
-from rdp import rdp
 
 # Load the dataset
 dataset = load_dataset("dwb2023/brain-tumor-image-dataset-semantic-segmentation", split="test")
-
-def simplify_segmentation(segmentation, max_points=20):
-    if not segmentation or len(segmentation) == 0:
-        return segmentation  # Return original if empty
-    epsilon = 1.0
-    simplified = rdp(np.array(segmentation), epsilon=epsilon)
-    while len(simplified) > max_points:
-        epsilon *= 1.5
-        simplified = rdp(np.array(segmentation), epsilon=epsilon)
-    return simplified.tolist()
+# print(f"Dataset loaded successfully. Number of images: {len(dataset)}")
 
 def draw_annotations(index):
     try:
@@ -36,16 +26,11 @@ def draw_annotations(index):
         bbox = record["bbox"]
         draw.rectangle([bbox[0], bbox[1], bbox[0] + bbox[2], bbox[1] + bbox[3]], outline="red", width=2)
 
-        # Draw original segmentation mask
+        # Draw segmentation mask
         segmentation = record["segmentation"]
         for seg in segmentation:
             draw.polygon(seg, outline="blue", width=2)
 
-        # Draw simplified segmentation
-        simplified_segmentation = [simplify_segmentation(seg) for seg in segmentation]
-        for seg in simplified_segmentation:
-            draw.polygon(seg, outline="green", width=2)
-
         # Prepare additional information
         category_id = record["category_id"]
         area = record["area"]
@@ -55,8 +40,7 @@ def draw_annotations(index):
         info += f"Image ID: {record['id']}\n"
         info += f"Category ID: {category_id}\n"
         info += f"Bounding Box: [{bbox[0]:.2f}, {bbox[1]:.2f}, {bbox[2]:.2f}, {bbox[3]:.2f}]\n"
-        info += f"Original Segmentation Points: {sum(len(seg) for seg in segmentation)}\n"
-        info += f"Simplified Segmentation Points: {sum(len(seg) for seg in simplified_segmentation)}\n"
+        info += f"Segmentation: {segmentation}\n"
         info += f"Area: {area:.2f}"
 
         return img, info
@@ -68,7 +52,6 @@ def draw_annotations(index):
 with gr.Blocks() as demo:
     gr.Markdown("# Brain Tumor Image Dataset Viewer")
     gr.Markdown("## Refer to the [dwb2023/brain-tumor-image-dataset-semantic-segmentation](https://huggingface.co/datasets/dwb2023/brain-tumor-image-dataset-semantic-segmentation/viewer/default/test) dataset for more information")
-    gr.Markdown("### Red: Bounding Box, Blue: Original Segmentation, Green: Simplified Segmentation (max 20 points)")
     
     with gr.Row():
         with gr.Column(scale=1):