def plot_txts_from_path(self, path):
if self.is_given_path_a_dir(path):
txt_files = self.getTxtFilesFromDirectory(path)
for txtFile in txt_files:
file_name = util.getLastTokenOfPath(txtFile)[0]
os.mkdir(file_name)
self.plot_txt_file(path + "/" + txtFile, file_name + "/" + file_name)
else:
file_name = util.getLastTokenOfPath(path)[0]
os.mkdir(file_name)
self.plot_txt_file(path, file_name + "/" + file_name)
def process(self, videoPath):
fileName = util.getLastTokenOfPath(videoPath)[0]
videoCutter = VideoCutter()
frames = videoCutter.cutVideo(videoPath, self.framesNro, self.rotate,
self.typeOfCut)
x = 1
edgeImages = []
for frame in frames:
print("Processing frame number " + str(x) + "...")
try:
treatedImage = self.detector.detectPersonFromNumpy(frame)
edgeImages.append(
self.edgeDetector.getImageBluryEdgesFromNumpy(
treatedImage))
print("Done.\n")
except:
print("Human not found on frame number " + str(x))
x = x + 1
if (len(edgeImages) > 0):
print("Concatenating all images")
directory = util.getPathOfVideoDirectory(videoPath)
data = util.combineImages(edgeImages)
util.saveImage(data, fileName + "Edges", ".jpg")
util.saveImageToPath(data, fileName + "Edges", ".jpg", directory)
print("Done.")
else:
print("Unsuccesful process, theres no human on the video clip " +
videoPath + "\n")
def process_from_path(path):
image = cv2.imread(path)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
classfier_path = "C:/Users/Jp/Desktop/brazo/data/cascade.xml" #"brazo_cascade.xml"
detector = cv2.CascadeClassifier(classfier_path)
rects = detector.detectMultiScale(gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(500, 500))
print(rects)
for (i, (x, y, w, h)) in enumerate(rects):
cv2.rectangle(image, (x, y), (x + w, y + h), (0, 0, 255), 2)
cv2.putText(image, "arm #{}".format(i + 1), (x, y - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 0, 255), 2)
file_name = util.getLastTokenOfPath(path)[0]
util.saveImageToPath(image, file_name + "cascade", ".jpg",
util.getPathOfVideoDirectory(path))
def process(self, video_path):
frames = self.cutVideo(video_path)
record = self.get_alike_weights(frames)
self.directory = util.getPathOfVideoDirectory(video_path)
self.videoName = util.getLastTokenOfPath(video_path)[0]
maxima_indexes, maxima_values, global_indexes = self.process_for_getting_max_alike(record)
print(maxima_indexes)
print(maxima_values)
print(global_indexes)
global_indexes = self.post_process_filter(frames, global_indexes)
if self.combineImages:
self.combine_frames(frames, global_indexes)
else:
self.save_critical_frames(frames, global_indexes)
def cutVideo(self, videoPath, outFramesNumber, rotate, typeOfCut):
cap = cv2.VideoCapture(videoPath)
videoName = util.getLastTokenOfPath(videoPath)
print("Video " + videoName[0] + " loaded")
#numero total de frames
frameCount = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
constantForProbablity = 5
cutOn = 0
cont = 0
listOfFrames = []
while (cap.isOpened()):
ret, frame = cap.read()
cont += 1
if cont >= cutOn:
#Rotar imagen
if rotate:
rotatedFrame = ndimage.rotate(frame, 270)
listOfFrames.append(rotatedFrame)
else:
listOfFrames.append(frame)
# Corte en el frame:
if typeOfCut == "Constant":
cutOn = frameCount / outFramesNumber + cont
if typeOfCut == "Probabilistic":
cutOn = frameCount / outFramesNumber + cont
cutOn = self.getRandomCut(cutOn, constantForProbablity)
if len(listOfFrames) == outFramesNumber:
break
else:
if cutOn >= frameCount:
break
cap.release()
return listOfFrames
def isGivenPathADir(self, path):
finalToken = util.getLastTokenOfPath(path)
return len(finalToken) == 1
def isGivenFileMP4File(self, file):
finalToken = util.getLastTokenOfPath(file)
return finalToken[1] == self.MP4_EXTENSION
def is_given_path_a_dir(self):
final_token = util.getLastTokenOfPath(self.path)
return len(final_token) == 1
def is_given_file_jpg_file(self, file):
final_token = util.getLastTokenOfPath(file)
return final_token[1] == self.JPG_EXTENSION
def combine_name(path, to_combine):
file_name, extension = util.getLastTokenOfPath(path)[:2]
new_file_name = file_name + to_combine + "." + extension
path = util.getPathOfVideoDirectory(path)
return path + new_file_name
def is_file_extension(file, extension):
final_token = util.getLastTokenOfPath(file)
return final_token[1] == extension