app.py

app.py

@@ -3,12 +3,10 @@ import gradio as gr
 from transformers import AutoModelForImageClassification, AutoImageProcessor
 from PIL import Image
 import torch
-from collections import Counter
 
 MODEL_LIST = [
     "prithivMLmods/Trash-Net",
-    "yangy50/garbage-classification",
-    "eunoiawiira/vgg-realwaste-classification"
+    "yangy50/garbage-classification"
 ]
 
 models = []
@@ -46,26 +44,24 @@ def classify_image(image: Image.Image):
         except Exception as e:
             results[model_name] = f"error:{e}"
 
-    # 格式化输出每个模型的结果
+    # 输出每个模型的结果
     results_text = "\n".join([f"{name}: {label}" for name, label in results.items()])
 
-    # 投票法计算最终标签
-    valid_labels = [lbl for lbl in results.values() if not lbl.startswith("error")]
-    final_label = Counter(valid_labels).most_common(1)[0][0] if valid_labels else "Unknown"
-    results_text += f"\n\nFinal Label (voting): {final_label}"
+    # 以 yangy50/garbage-classification 为最终结果
+    final_label = results.get("yangy50/garbage-classification", "Unknown")
+    results_text += f"\n\nFinal Label (base yangy50): {final_label}"
     return results_text
 
 iface = gr.Interface(
     fn=classify_image,
     inputs=gr.Image(type="pil", label="Upload Image"),
     outputs=[gr.Textbox(label="Model Predictions")],
-    title="Multi-Model Trash Classification",
+    title="Trash Classification",
     description=(
         "Upload an image, and the following models will classify it:\n"
         "1. prithivMLmods/Trash-Net\n"
         "2. yangy50/garbage-classification\n"
-        "3. eunoiawiira/vgg-realwaste-classification\n"
-        "The final label is determined by majority vote."
+        "The final label is based on yangy50/garbage-classification."
     )
 )