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Mitul Mohammad Abdullah Al Mukit
commited on
Commit
•
1c82367
1
Parent(s):
53bab76
attempt to fix resize bug
Browse files
demo.py
CHANGED
@@ -6,6 +6,7 @@ import imageSegmentation
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from mediapipe.tasks.python import vision
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import Visualization_utilities as vis
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# Get a reference to webcam #0 (the default one)
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# video_capture = cv2.VideoCapture(0)
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@@ -79,10 +80,16 @@ def process_frame(frame, process_this_frame, face_locations, faces, face_names,
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if process_this_frame:
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face_names = []
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# Resize frame of video to 1/4 size for faster face recognition processing
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-
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# Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
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rgb_small_frame = cv2.cvtColor(
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# Find all the faces and face encodings in the current frame of video
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face_locations = face_recognition.face_locations(rgb_small_frame)
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@@ -135,10 +142,10 @@ def process_frame(frame, process_this_frame, face_locations, faces, face_names,
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for (top, right, bottom, left), name in zip(face_locations, face_names):
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# Scale back up face locations since the frame we detected in was scaled to 1/4 size
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top *= 4
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right *= 4
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bottom *= 4
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left *= 4
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# Draw a box around the face
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cv2.rectangle(frame, (left, top), (right, bottom), (65, 181, 41), 4)
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from mediapipe.tasks.python import vision
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import Visualization_utilities as vis
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import time
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# Get a reference to webcam #0 (the default one)
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# video_capture = cv2.VideoCapture(0)
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if process_this_frame:
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face_names = []
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# Resize frame of video to 1/4 size for faster face recognition processing
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# if frame != None:
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# print(f'frame: {len(frame)}')
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# try:
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# small_frame = cv2.imread(image_dir)
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# small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
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# else:
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# print('fram has nth')
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# Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
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rgb_small_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # edited
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# Find all the faces and face encodings in the current frame of video
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face_locations = face_recognition.face_locations(rgb_small_frame)
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for (top, right, bottom, left), name in zip(face_locations, face_names):
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# Scale back up face locations since the frame we detected in was scaled to 1/4 size
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# top *= 4
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# right *= 4
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# bottom *= 4
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# left *= 4
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# Draw a box around the face
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cv2.rectangle(frame, (left, top), (right, bottom), (65, 181, 41), 4)
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