128 lines
4.7 KiB
Python
128 lines
4.7 KiB
Python
import imageio
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import imutils
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import numpy as np
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from Layer import Layer
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import cv2
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from VideoReader import VideoReader
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import pickle
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class Exporter:
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fps = 30
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def __init__(self, config):
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self.footagePath = config["inputPath"]
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self.outputPath = config["outputPath"]
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self.resizeWidth = config["resizeWidth"]
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self.config = config
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print("Exporter initiated")
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def export(self):
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fps = self.fps
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writer = imageio.get_writer(outputPath, fps=fps)
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for frame in frames:
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writer.append_data(np.array(frame))
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writer.close()
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def exportLayers(self, layers):
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listOfFrames = self.makeListOfFrames(layers)
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videoReader = VideoReader(self.config, listOfFrames)
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videoReader.fillBuffer()
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maxLength = self.getMaxLengthOfLayers(layers)
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underlay = cv2.VideoCapture(self.footagePath).read()[1]
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underlay = cv2.cvtColor(underlay, cv2.COLOR_BGR2RGB)
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frames = [underlay]*maxLength
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exportFrame = 0
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self.fps = videoReader.getFPS()
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writer = imageio.get_writer(self.outputPath, fps=self.fps)
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while not videoReader.videoEnded():
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frameCount, frame = videoReader.pop()
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if frameCount % (60*self.fps) == 0:
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print("Minutes processed: ", frameCount/(60*self.fps))
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if frame is None:
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print("ContourExtractor: frame was None")
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continue
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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frame2 = underlay
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for layer in layers:
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if layer.startFrame <= frameCount and layer.startFrame + len(layer.bounds) > frameCount:
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for (x, y, w, h) in layer.bounds[frameCount - layer.startFrame]:
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factor = videoReader.w / self.resizeWidth
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x = int(x * factor)
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y = int(y * factor)
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w = int(w * factor)
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h = int(h * factor)
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frame2[y:y+h, x:x+w] = frame[y:y+h, x:x+w]
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writer.append_data(frame2)
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videoReader.thread.join()
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def exportOverlayed(self, layers):
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listOfFrames = self.makeListOfFrames(layers)
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videoReader = VideoReader(self.config, listOfFrames)
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videoReader.fillBuffer()
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maxLength = self.getMaxLengthOfLayers(layers)
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underlay = cv2.VideoCapture(self.footagePath).read()[1]
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underlay = cv2.cvtColor(underlay, cv2.COLOR_BGR2RGB)
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frames = [underlay]*maxLength
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exportFrame = 0
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while not videoReader.videoEnded():
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frameCount, frame = videoReader.pop()
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if frameCount % (60*self.fps) == 0:
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print("Minutes processed: ", frameCount/(60*self.fps))
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if frame is None:
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print("ContourExtractor: frame was None")
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continue
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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for layer in layers:
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if layer.startFrame <= frameCount and layer.startFrame + len(layer.bounds) > frameCount:
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for (x, y, w, h) in layer.bounds[frameCount - layer.startFrame]:
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factor = videoReader.w / self.resizeWidth
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x = int(x * factor)
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y = int(y * factor)
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w = int(w * factor)
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h = int(h * factor)
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# if exportFrame as index instead of frameCount - layer.startFrame then we have layer after layer
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frame2 = frames[frameCount - layer.startFrame]
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frame2[y:y+h, x:x+w] = frame[y:y+h, x:x+w]
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frames[frameCount - layer.startFrame] = np.copy(frame2)
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videoReader.thread.join()
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self.fps = videoReader.getFPS()
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fps = self.fps
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writer = imageio.get_writer(self.outputPath, fps=fps)
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for frame in frames:
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writer.append_data(frame)
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writer.close()
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def exportRawData(self, layers):
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with open(self.outputPath.split(".")[-2] + ".txt", "wb+") as file:
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pickle.dump(layers, file)
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def getMaxLengthOfLayers(self, layers):
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maxLength = 0
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for layer in layers:
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if layer.getLength() > maxLength:
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maxLength = layer.getLength()
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return maxLength
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def makeListOfFrames(self, layers):
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'''Returns set of all Frames which are relavant to the Layers'''
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frameNumbers = set()
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for layer in layers:
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frameNumbers.update(
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list(range(layer.startFrame, layer.startFrame + len(layer.bounds))))
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return list(frameNumbers)
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