Update app.py

app.py

@@ -1,38 +1,96 @@
+# import cv2
+# import streamlit as st
+# from streamlit_webrtc import webrtc_streamer, VideoHTMLAttributes
+# import numpy as np
+# import av
+
+# st.title("OpenCV Filters on Video Stream")
+
+# filter = "none"
+
+
+# def transform(frame: av.VideoFrame):
+#     img = frame.to_ndarray(format="bgr24")
+
+#     if filter == "blur":
+#         img = cv2.GaussianBlur(img, (21, 21), 0)
+#     elif filter == "canny":
+#         img = cv2.cvtColor(cv2.Canny(img, 100, 200), cv2.COLOR_GRAY2BGR)
+#     elif filter == "grayscale":
+#         # We convert the image twice because the first conversion returns a 2D array.
+#         # the second conversion turns it back to a 3D array.
+#         img = cv2.cvtColor(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), cv2.COLOR_GRAY2BGR)
+#     elif filter == "sepia":
+#         kernel = np.array(
+#             [[0.272, 0.534, 0.131], [0.349, 0.686, 0.168], [0.393, 0.769, 0.189]]
+#         )
+#         img = cv2.transform(img, kernel)
+#     elif filter == "invert":
+#         img = cv2.bitwise_not(img)
+#     elif filter == "none":
+#         pass
+
+#     return av.VideoFrame.from_ndarray(img, format="bgr24")
+
+
+# col1, col2, col3, col4, col5, col6 = st.columns([1, 1, 1, 1, 1, 1])
+
+# with col1:
+#     if st.button("None"):
+#         filter = "none"
+# with col2:
+#     if st.button("Blur"):
+#         filter = "blur"
+# with col3:
+#     if st.button("Grayscale"):
+#         filter = "grayscale"
+# with col4:
+#     if st.button("Sepia"):
+#         filter = "sepia"
+# with col5:
+#     if st.button("Canny"):
+#         filter = "canny"
+# with col6:
+#     if st.button("Invert"):
+#         filter = "invert"
+
+
+# webrtc_streamer(
+#     key="streamer",
+#     video_frame_callback=transform,
+#     sendback_audio=False
+#     )
+
 import cv2
 import streamlit as st
-from streamlit_webrtc import webrtc_streamer, VideoHTMLAttributes
+from streamlit_webrtc import webrtc_streamer
 import numpy as np
 import av
 
 st.title("OpenCV Filters on Video Stream")
 
+# Define the filter state variable
 filter = "none"
 
-
 def transform(frame: av.VideoFrame):
     img = frame.to_ndarray(format="bgr24")
 
+    # Apply the selected filter
     if filter == "blur":
         img = cv2.GaussianBlur(img, (21, 21), 0)
     elif filter == "canny":
         img = cv2.cvtColor(cv2.Canny(img, 100, 200), cv2.COLOR_GRAY2BGR)
     elif filter == "grayscale":
-        # We convert the image twice because the first conversion returns a 2D array.
-        # the second conversion turns it back to a 3D array.
         img = cv2.cvtColor(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), cv2.COLOR_GRAY2BGR)
     elif filter == "sepia":
-        kernel = np.array(
-            [[0.272, 0.534, 0.131], [0.349, 0.686, 0.168], [0.393, 0.769, 0.189]]
-        )
+        kernel = np.array([[0.272, 0.534, 0.131], [0.349, 0.686, 0.168], [0.393, 0.769, 0.189]])
         img = cv2.transform(img, kernel)
     elif filter == "invert":
         img = cv2.bitwise_not(img)
-    elif filter == "none":
-        pass
-
+    
     return av.VideoFrame.from_ndarray(img, format="bgr24")
 
-
+# Streamlit buttons to choose filters
 col1, col2, col3, col4, col5, col6 = st.columns([1, 1, 1, 1, 1, 1])
 
 with col1:
@@ -54,9 +112,10 @@ with col6:
     if st.button("Invert"):
         filter = "invert"
 
-
+# Display the video stream
 webrtc_streamer(
     key="streamer",
     video_frame_callback=transform,
     sendback_audio=False
-    )
+)
+