delete nms add description

app.py

@@ -22,7 +22,8 @@ predictor = Predictor(
 )
 
 
-def image_inference(image, confthre, nmsthre):
+def image_inference(image, confthre):
+    nmsthre = 0.01
     cv2.cvtColor(image, cv2.COLOR_RGB2BGR, image)
     outputs, img_info = predictor.inference(image, confthre, nmsthre)
     result_image = predictor.visual(outputs[0], img_info)
@@ -34,18 +35,18 @@ image_interface = gr.Interface(
     fn=image_inference,
     inputs=[
         "image",
-        gr.Slider(0.01, 1, value=0.4, step=0.01, label="Confidence Threshold", ),
-        gr.Slider(0.01, 1, value=0.01, step=0.01, label="NMS Threshold")
+        gr.Slider(0.01, 1, value=0.4, step=0.01, label="Confidence Threshold", )
     ],
-    examples=[["assets/sample.png", 0.4, 0.01], ["assets/sample4.jpg", 0.4, 0.01],
-              ["assets/sample5.jpg", 0.4, 0.01], ["assets/sample6.jpg", 0.4, 0.01],
-              ["assets/sample7.jpg", 0.4, 0.01], ["assets/sample8.jpg", 0.4, 0.01]],
+    examples=[["assets/sample.png", 0.4], ["assets/sample4.jpg", 0.4],
+              ["assets/sample5.jpg", 0.4], ["assets/sample6.jpg", 0.4],
+              ["assets/sample7.jpg", 0.4], ["assets/sample8.jpg", 0.4]],
     outputs=gr.Image(type="pil"),
-    title="OpenLenda image demo"
+    title="OpenLenda image demo",
+    description="You can upload your own image. Use the slider to adjust the confidence threshold. Example images are good for looking at the ability of the model.<br>自由に画像をアップロードできます。スライダーで信頼度の閾値を調整できます。サンプル画像はモデルの能力を見るのにおすすめの画像達です。",
 )
 
 
-def video_inference(video_file, confthre, nmsthre, start_sec, duration):
+def video_inference(video_file, confthre, start_sec, duration):
     start_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec))
     end_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec + duration))
 
@@ -74,6 +75,7 @@ def video_inference(video_file, confthre, nmsthre, start_sec, duration):
             except Exception as e:
                 print(e)
                 continue
+            nmsthre = 0.01
             outputs, img_info = predictor.inference(frame, confthre, nmsthre)
             result_frame = predictor.visual(outputs[0], img_info)
             out.write(result_frame)
@@ -94,12 +96,12 @@ video_interface = gr.Interface(
     inputs=[
         gr.Video(),
         gr.Slider(0.01, 1, value=0.5, step=0.01, label="Confidence Threshold", ),
-        gr.Slider(0.01, 1, value=0.01, step=0.01, label="NMS Threshold"),
         gr.Slider(0, 60, value=0, step=1, label="Start Second"),
         gr.Slider(1, 10, value=3, step=1, label="Duration"),
     ],
     outputs=gr.Video(),
-    title="OpenLenda video demo"
+    title="OpenLenda video demo",
+    description="You can upload your own video. Use the slider to adjust the confidence threshold, start second, and duration.<br>自由に動画をアップロードできます。スライダーで信頼度の閾値、開始秒数、動画の長さを調整できます。",
 )
 
 if __name__ == "__main__":