142 lines
5.5 KiB
Python
142 lines
5.5 KiB
Python
import imageio
|
|
import imutils
|
|
import numpy as np
|
|
from Application.Layer import Layer
|
|
import cv2
|
|
from Application.VideoReader import VideoReader
|
|
import pickle
|
|
|
|
class Exporter:
|
|
fps = 30
|
|
|
|
def __init__(self, config):
|
|
self.footagePath = config["inputPath"]
|
|
self.outputPath = config["outputPath"]
|
|
self.resizeWidth = config["resizeWidth"]
|
|
self.config = config
|
|
print("Exporter initiated")
|
|
|
|
def export(self, layers, raw = True, layered = False, overlayed = True):
|
|
|
|
if raw:
|
|
self.exportRawData(layers)
|
|
if layered and overlayed:
|
|
print("Layered and Individual are mutially exclusive, Individual was choosen automatically")
|
|
overlayed = False
|
|
if layered and not overlayed:
|
|
self.exportLayers(layers)
|
|
if overlayed and not layered:
|
|
self.exportOverlayed(layers)
|
|
|
|
|
|
def exportLayers(self, layers):
|
|
|
|
listOfFrames = self.makeListOfFrames(layers)
|
|
videoReader = VideoReader(self.config, listOfFrames)
|
|
videoReader.fillBuffer()
|
|
maxLength = self.getMaxLengthOfLayers(layers)
|
|
underlay = cv2.VideoCapture(self.footagePath).read()[1]
|
|
underlay = cv2.cvtColor(underlay, cv2.COLOR_BGR2RGB)
|
|
frames = [underlay]*maxLength
|
|
exportFrame = 0
|
|
|
|
self.fps = videoReader.getFPS()
|
|
writer = imageio.get_writer(self.outputPath, fps=self.fps)
|
|
while not videoReader.videoEnded():
|
|
frameCount, frame = videoReader.pop()
|
|
if frameCount % (60*self.fps) == 0:
|
|
print("Minutes processed: ", frameCount/(60*self.fps))
|
|
if frame is None:
|
|
print("ContourExtractor: frame was None")
|
|
continue
|
|
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
|
|
|
|
frame2 = np.copy(underlay)
|
|
for layer in layers:
|
|
if layer.startFrame <= frameCount and layer.startFrame + len(layer.bounds) > frameCount:
|
|
for (x, y, w, h) in layer.bounds[frameCount - layer.startFrame]:
|
|
if x is None:
|
|
break
|
|
factor = videoReader.w / self.resizeWidth
|
|
x = int(x * factor)
|
|
y = int(y * factor)
|
|
w = int(w * factor)
|
|
h = int(h * factor)
|
|
|
|
frame2[y:y+h, x:x+w] = np.copy(frame[y:y+h, x:x+w])
|
|
cv2.putText(frame2, str(int(frameCount/self.fps)), (int(x+w/2), int(y+h/2)), cv2.FONT_HERSHEY_SIMPLEX, 1,(255,255,255), 2)
|
|
writer.append_data(frame2)
|
|
|
|
|
|
videoReader.thread.join()
|
|
|
|
|
|
def exportOverlayed(self, layers):
|
|
|
|
listOfFrames = self.makeListOfFrames(layers)
|
|
videoReader = VideoReader(self.config, listOfFrames)
|
|
videoReader.fillBuffer()
|
|
maxLength = self.getMaxLengthOfLayers(layers)
|
|
underlay = cv2.VideoCapture(self.footagePath).read()[1]
|
|
underlay = cv2.cvtColor(underlay, cv2.COLOR_BGR2RGB)
|
|
frames = [underlay]*maxLength
|
|
exportFrame = 0
|
|
|
|
|
|
while not videoReader.videoEnded():
|
|
frameCount, frame = videoReader.pop()
|
|
if frameCount % (60*self.fps) == 0:
|
|
print("Minutes processed: ", frameCount/(60*self.fps))
|
|
if frame is None:
|
|
print("ContourExtractor: frame was None")
|
|
continue
|
|
|
|
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
|
|
for layer in layers:
|
|
if layer.startFrame <= frameCount and layer.startFrame + len(layer.bounds) > frameCount:
|
|
for (x, y, w, h) in layer.bounds[frameCount - layer.startFrame]:
|
|
if x is None:
|
|
break
|
|
factor = videoReader.w / self.resizeWidth
|
|
x = int(x * factor)
|
|
y = int(y * factor)
|
|
w = int(w * factor)
|
|
h = int(h * factor)
|
|
# if exportFrame as index instead of frameCount - layer.startFrame then we have layer after layer
|
|
frame2 = frames[frameCount - layer.startFrame]
|
|
frame2[y:y+h, x:x+w] = frame2[y:y+h, x:x+w]/2 + frame[y:y+h, x:x+w]/2
|
|
|
|
frames[frameCount - layer.startFrame] = np.copy(frame2)
|
|
cv2.putText(frames[frameCount - layer.startFrame], str(int(frameCount/self.fps)), (int(x+w/2), int(y+h/2)), cv2.FONT_HERSHEY_SIMPLEX, 1,(255,255,255), 2)
|
|
|
|
videoReader.thread.join()
|
|
|
|
self.fps = videoReader.getFPS()
|
|
fps = self.fps
|
|
writer = imageio.get_writer(self.outputPath, fps=fps)
|
|
for frame in frames:
|
|
writer.append_data(frame)
|
|
|
|
writer.close()
|
|
|
|
def exportRawData(self, layers):
|
|
with open(self.outputPath.split(".")[-2] + ".txt", "wb+") as file:
|
|
pickle.dump(layers, file)
|
|
|
|
|
|
def getMaxLengthOfLayers(self, layers):
|
|
maxLength = 0
|
|
for layer in layers:
|
|
if layer.getLength() > maxLength:
|
|
maxLength = layer.getLength()
|
|
return maxLength
|
|
|
|
def makeListOfFrames(self, layers):
|
|
'''Returns set of all Frames which are relavant to the Layers'''
|
|
frameNumbers = set()
|
|
for layer in layers:
|
|
frameNumbers.update(
|
|
list(range(layer.startFrame, layer.startFrame + len(layer.bounds))))
|
|
|
|
return sorted(list(frameNumbers))
|