wip

Author: ks6088ts

apps/99_streamlit_examples/pages/12_Video_processing.py

@@ -7,13 +7,20 @@
 
 
 class Processor:
-    def __init__(self, model_name):
+    def __init__(
+        self,
+        model_name: str,
+    ):
         self.model = YOLO(model_name)
 
-    def process(self, frame):
+    def process(
+        self,
+        frame: cv2.UMat,
+        confidence: float,
+    ) -> cv2.UMat:
         results = self.model(
             frame,
-            conf=0.5,
+            conf=confidence,
             classes=[0],
         )
         output_img = results[0].plot(
@@ -27,24 +34,33 @@ def process(self, frame):
 
 
 with st.sidebar:
+    # model_name: https://docs.ultralytics.com/models/yolov8/#supported-tasks-and-modes
     model_name = st.selectbox(
         label="Select a model",
         options=[
             "yolov8n.pt",
             "yolov9c.pt",
             "yolov10n.pt",
-            # https://docs.ultralytics.com/models/yolov8/#supported-tasks-and-modes
         ],
         key="model_name",
         index=0,
     )
+    # device: https://docs.opencv.org/4.10.0/d8/dfe/classcv_1_1VideoCapture.html#a5d5f5dacb77bbebdcbfb341e3d4355c1
     device = st.text_input(
         label="input your video/camera device",
         value="0",
     )
     if device.isnumeric():
         # e.g. "0" -> 0
         device = int(device)
+    # confidence: https://docs.ultralytics.com/usage/cfg/#predict-settings
+    confidence = st.slider(
+        label="Confidence",
+        min_value=0.0,
+        max_value=1.0,
+        value=0.5,
+        step=0.01,
+    )
 
 st.title("Video processing")
 
@@ -68,6 +84,7 @@ def process(self, frame):
 
         processed_frame = processor.process(
             frame=frame,
+            confidence=confidence,
         )
 
         image_loc.image(