Update app.py

app.py

@@ -25,15 +25,8 @@ mushroom_species = {
 }
 
 # 🎨 Image preprocessing
-# ✅ Define transforms for training and validation
-train_transform = transforms.Compose([
-    transforms.Resize((256, 256)),
-    transforms.RandomResizedCrop(224, scale=(0.8, 1.0)),
-    transforms.RandomHorizontalFlip(p=0.5),
-    transforms.RandomVerticalFlip(p=0.3),
-    transforms.RandomRotation(degrees=45),
-    transforms.ColorJitter(brightness=0.3, contrast=0.3, saturation=0.2, hue=0.05),
-    transforms.RandomAffine(degrees=0, translate=(0.1, 0.1), scale=(0.9, 1.1)),
+transform = transforms.Compose([
+    transforms.Resize((224, 224)),
     transforms.ToTensor(),
     transforms.Normalize([0.485, 0.456, 0.406],
                          [0.229, 0.224, 0.225])
@@ -60,7 +53,7 @@ def classify_mushroom(image: Image.Image):
         if score < CONFIDENCE_THRESHOLD:
             label = "Uncertain"
 
-        return label, ("กินได้" if label == "Edible" else ("พิษ" if label == "Poisonous" else "ไม่มั่นใจ (Confidence score < 85%)")), f"{score:.2f}%", suggestion
+        return label, ("กินได้" if label == "Edible" else ("พิษ" if label == "Poisonous" else "ไม่มั่นใจ")), f"{score:.2f}%", suggestion
 
     except Exception as e:
         print(f"❌ Error: {e}")
@@ -77,8 +70,7 @@ if __name__ == "__main__":
         gr.Markdown("Upload a mushroom photo or use your camera to check if it’s edible or poisonous.\nอัปโหลดรูปเห็ดหรือใช้กล้องเพื่อตรวจสอบว่าเห็ดกินได้หรือมีพิษ")
 
         with gr.Row():
-            image_input = gr.Image(type="pil", label="📷 Upload or Capture Mushroom Image")  
-            with gr.Column():
+            image_input = gr.Image(type="pil", label="📷 Upload or Capture Mushroom Image") 
                 label_en = gr.Textbox(label="🧬 Prediction (English)")
                 label_th = gr.Textbox(label="🔁 คำทำนาย (ภาษาไทย)")
                 confidence = gr.Textbox(label="📶 Confidence Score")