Update app.py

app.py

@@ -3,6 +3,9 @@ from PIL import Image
 import gradio as gr
 import numpy
 import torch
+import os
+
+os.system('pip install git+https://github.com/fcakyon/ultralyticsplus.git')
 
 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"
@@ -87,7 +90,7 @@ def sahi_yolov5_inference(
 
         model = YOLO('SerdarHelli/deprem_satellite_labeled_yolov8')
         result = model.predict(image, imgsz=image_size)[0]
-        render = render_result(model=model, image=image, result=result, rect_th=rect_th, text_th=text_th)
+        render = render_result(model=model, image=image, result=result)
         return render
     
     elif model_type == "YOLOv7":
@@ -128,7 +131,7 @@ examples = [
     ["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/Istanbul.jpg", 'kadirnar/UNet-EfficientNet-b6-Istanbul', "Unet-Istanbul", 512, 512, 512, 0.1, 0.1, "NMS", "IOU", 0.25, False],
 ]
 
 
@@ -141,7 +144,7 @@ demo = gr.Interface(
     article=article,
     examples=examples,
     theme="huggingface",
-    cache_examples=True,
+    cache_examples=False,
 )
 
 demo.launch(debug=True, enable_queue=True)

requirements.txt

@@ -2,6 +2,5 @@ torch==1.7.1
 yolov5==7.0.8
 sahi==0.11.11
 yolov7detect==1.0.1
-ultralyticsplus==0.0.26
 segmentation-models-pytorch==0.1.3
 albumentations==1.3.0