use LAB color space
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11cae0e6f5
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@ -16,8 +16,8 @@ class ContourExtractor:
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#X = {frame_number: [(contour, (x,y,w,h)), ...], }
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extractedContours = dict()
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min_area = 500
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max_area = 5000
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threashold = 20
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max_area = 7000
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threashold = 13
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xDim = 0
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yDim = 0
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@ -51,8 +51,10 @@ class ContourExtractor:
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frame = imutils.resize(frame, width=resizeWidth)
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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gray = cv2.GaussianBlur(gray, (5, 5), 0)
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2LAB)
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gray = np.asarray(gray[:,:,1]/2 + gray[:,:,2]/2).astype(np.uint8)
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#gray = cv2.GaussianBlur(gray, (5, 5), 0)
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# if the first frame is None, initialize it
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if firstFrame is None:
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@ -60,6 +62,7 @@ class ContourExtractor:
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continue
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frameDelta = cv2.absdiff(gray, firstFrame)
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thresh = cv2.threshold(frameDelta, threashold, 255, cv2.THRESH_BINARY)[1]
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# dilate the thresholded image to fill in holes, then find contours
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thresh = cv2.dilate(thresh, None, iterations=3)
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@ -78,9 +81,12 @@ class ContourExtractor:
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#cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
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if len(contours) != 0:
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extractedContours[frameCount] = contours
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if frameCount % (60*30) == 0:
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print("Minutes processed: ", frameCount/(60*30))
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frameCount += 1
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#cv2.imshow( "annotated", frame )
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#cv2.imshow( "annotated", thresh )
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#cv2.waitKey(10) & 0XFF
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self.extractedContours = extractedContours
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return extractedContours
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14
Exporter.py
14
Exporter.py
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@ -16,19 +16,21 @@ class Exporter:
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writer.append_data(np.array(frame))
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writer.close()
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def exportLayers(self, layers, outputPath):
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def exportLayers(self,underlay, layers, outputPath, resizeWidth):
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fps = self.fps
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writer = imageio.get_writer(outputPath, fps=fps)
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i=0
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for layer in layers:
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data = layer.data
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contours = layer.bounds
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if len(data) < 10:
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continue
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for frame in data:
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(x, y, w, h) = frame[1]
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frame = frame[0]
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frame1 = np.zeros(shape=[1080, 1920, 3], dtype=np.uint8)
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frame1 = imutils.resize(frame1, width=512)
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for frame, contour in zip(data, contours):
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(x, y, w, h) = contour
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frame = frame
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frame1 = underlay
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frame1 = imutils.resize(frame1, width=resizeWidth)
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frame1 = cv2.cvtColor(frame1, cv2.COLOR_BGR2RGB)
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frame1[y:y+frame.shape[0], x:x+frame.shape[1]] = frame
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cv2.putText(frame1, str(i), (30,30), cv2.FONT_HERSHEY_SIMPLEX, 1,(255,255,255), 2)
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writer.append_data(np.array(frame1))
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@ -47,7 +47,7 @@ class LayerFactory:
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print("LayerFactory: Layer knew no bounds")
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continue
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if frameNumber - layer.lastFrame <= 20:
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if frameNumber - layer.lastFrame <= 5:
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(x2,y2,w2,h2) = layer.bounds[-1]
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if self.contoursOverlay((x-tol,y+h+tol), (x+w+tol,y-tol), (x2,y2+h2), (x2+w2,y2)):
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foundLayer = True
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6
main.py
6
main.py
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@ -10,10 +10,10 @@ import cv2
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def demo():
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print("startup")
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resizeWidth = 512
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maxLayerLength = 5*50*30
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maxLayerLength = 1*60*30
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start = time.time()
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footagePath = os.path.join(os.path.dirname(__file__), "./generate test footage/3.MP4")
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footagePath = os.path.join(os.path.dirname(__file__), "./generate test footage/out.mp4")
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contours = ContourExtractor().extractContours(footagePath, resizeWidth)
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print("Time consumed in working: ", time.time() - start)
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layerFactory = LayerFactory(contours)
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@ -21,7 +21,7 @@ def demo():
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layerFactory.sortLayers()
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layerFactory.fillLayers(footagePath)
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underlay = cv2.VideoCapture(footagePath).read()[1]
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Exporter().exportOverlayed(underlay, layerFactory.layers, os.path.join(os.path.dirname(__file__), "./short.mp4"), resizeWidth)
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Exporter().exportLayers(underlay, layerFactory.layers, os.path.join(os.path.dirname(__file__), "./short.mp4"), resizeWidth)
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print("Total time: ", time.time() - start)
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def init():
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print("not needed yet")
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