Update app.py

app.py

@@ -6,7 +6,7 @@ import torch
 
 model_id_list = ['deprem-ml/Binafarktespit-yolo5x-v1-xview', 'SerdarHelli/deprem_satellite_labeled_yolov8', 'kadirnar/yolov7-v0.1', 'kadirnar/UNet-EfficientNet-b6-Istanbul']
 current_device = "cuda" if torch.cuda.is_available() else "cpu"
-model_types = ["YOLOv5", "YOLOv5 + SAHI", "YOLOv8", "YOLOv7", "Unet-Istanbul"]
+model_types = ["YOLOv5", "YOLOv5 + SAHI", "YOLOv8", "YOLOv7"]
 
 def sahi_yolov5_inference(
     image,
@@ -97,11 +97,13 @@ def sahi_yolov5_inference(
         results = model([image], size=image_size)
         return results.render()[0]
 
+    """
     elif model_type == "Unet-Istanbul":
         from istanbul_unet import unet_prediction
         
         output = unet_prediction(input_path=image, model_path=model_id)
         return output
+    """
     
 inputs = [
     gr.Image(type="pil", label="Original Image"),
@@ -127,8 +129,8 @@ examples = [
     ["data/26.jpg", 'deprem-ml/Binafarktespit-yolo5x-v1-xview', "YOLOv5 + SAHI", 640, 512, 512, 0.1, 0.1, "NMS", "IOU", 0.25, False],
     ["data/27.jpg", 'deprem-ml/Binafarktespit-yolo5x-v1-xview', "YOLOv5 + SAHI", 640, 512, 512, 0.1, 0.1, "NMS", "IOU", 0.25, False],
     ["data/28.jpg", 'deprem-ml/Binafarktespit-yolo5x-v1-xview', "YOLOv5 + SAHI", 640, 512, 512, 0.1, 0.1, "NMS", "IOU", 0.25, False],
-    ["data/31.jpg", 'deprem-ml/SerdarHelli-yolov8-v1-xview', "YOLOv8", 640, 512, 512, 0.1, 0.1, "NMS", "IOU", 0.25, False],
-    ["data/Istanbul.jpg", 'kadirnar/UNet-EfficientNet-b6-Istanbul', "Unet-Istanbul", 512, 512, 512, 0.1, 0.1, "NMS", "IOU", 0.25, False],
+    ["data/31.jpg", 'deprem-ml/SerdarHelli-yolov8-v1-xview', "YOLOv8", 640, 512, 512, 0.1, 0.1, "NMS", "IOU", 0.25, False]
+    #["data/Istanbul.jpg", 'kadirnar/UNet-EfficientNet-b6-Istanbul', "Unet-Istanbul", 512, 512, 512, 0.1, 0.1, "NMS", "IOU", 0.25, False],
 ]