def open(self, filename):
"""Open the video file and attach it to the class.
Takes:
filename - the full path to the video
Gives:
isOpened - True if opened, False otherwise
"""
if filename is not None:
self.filename = filename
ext = filename.split('.')[-1]
if ext in ['tiff', 'tif', 'TIF', 'TIFF']:
# For tiffs use tiffcapture
self.format = 'TIFF'
self.video = tc.opentiff(filename)
self._is_open = True
self.length = self.video.length
self.shape = self.video.shape
self._curr = 0
else:
# For other formats try opencv
self.format = 'CV'
self.video = cv2.VideoCapture(filename)
self._is_open = True
self.length = self.video.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT)
self.shape = (
int(self.video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)),
int(self.video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)))
self._curr = 0
return self.isOpened()
def __init__(self, video_source=0):
# Open the video source
self.vid = tc.opentiff(video_source)
if not self.vid.isOpened():
raise ValueError("Unable to open video source", video_source)
self.vid_copy = cv2.VideoCapture(video_source)
self.end = False
# Get video source width and height
self.width = self.vid_copy.get(cv2.CAP_PROP_FRAME_WIDTH)
self.height = self.vid_copy.get(cv2.CAP_PROP_FRAME_HEIGHT)
self.frame_counter = 0
self.num_frames = 0
def loadImageStackFromFile(self, fileName=''):
""" Load an image stack from file.
Without any arguments, loadImageStackFromFile() will popup a file dialog to choose the image file.
With a fileName argument, loadImageStackFromFile(fileName) will attempt to load the specified file directly.
"""
if len(fileName) == 0:
if QT_VERSION_STR[0] == '4':
fileName = QFileDialog.getOpenFileName(self, "Open TIFF stack file.")
elif QT_VERSION_STR[0] == '5':
fileName, dummy = QFileDialog.getOpenFileName(self, "Open TIFF stack file.")
fileName = str(fileName)
if len(fileName) and os.path.isfile(fileName):
self._tiffCaptureHandle = tiffcapture.opentiff(fileName)
self.showFrame(0)
def loadImageStackFromFile(self, fileName=''):
""" Load an image stack from file.
Without any arguments, loadImageStackFromFile() will popup a file dialog to choose the image file.
With a fileName argument, loadImageStackFromFile(fileName) will attempt to load the specified file directly.
"""
if len(fileName) == 0:
if QT_VERSION_STR[0] == '4':
fileName = QFileDialog.getOpenFileName(
self, "Open TIFF stack file.")
elif QT_VERSION_STR[0] == '5':
fileName, dummy = QFileDialog.getOpenFileName(
self, "Open TIFF stack file.")
fileName = str(fileName)
if len(fileName) and os.path.isfile(fileName):
self._tiffCaptureHandle = tiffcapture.opentiff(fileName)
self.showFrame(0)
def filePacker(filePath,versionId, patientId, testId, frameWidth, frameHeight, frameNumber, decayPoint, heatingPoint,outFile):
dateTimeObj = datetime.now()
now = dateTimeObj.strftime("%d%m%Y%H%M%S")#ddMMyyyyHHmmss
dateX = now.encode(encoding = 'ascii',errors='strict')
tiff = tc.opentiff(filePath) #open img
outputFile = open(outFile,"wb")
outputFile.write(struct.pack('B',versionId))
outputFile.write(struct.pack('i',patientId))
outputFile.write(struct.pack('i',testId))
outputFile.write(struct.pack('14B',*dateX))
outputFile.write(struct.pack('i',frameWidth))
outputFile.write(struct.pack('i',frameHeight))
outputFile.write(struct.pack('i',frameNumber))
outputFile.write(struct.pack('i',decayPoint))
outputFile.write(struct.pack('i',heatingPoint))
frameLooper(tiff,outputFile,frameWidth,frameHeight)
outputFile.close()
def main():
print(sys.argv[1])
tiff = tc.opentiff(sys.argv[1])
print(sys.getsizeof(open(sys.argv[1])))
i = 0
for img in tiff:
if i ==30:
print(sys.getsizeof(img))
img_arr = np.array(img, dtype='int64')
print(img_arr[103,110])
img_arr = img_arr - 27315
print(img_arr[103, 110])
dt = np.dtype('int16')
img_arr = np.array(img, dtype=dt)
print(img_arr[103, 110])
img_arr= img_arr - 27315
print(img_arr[103, 110])
i += 1
def __init__(self, path, debug, output_name, windows_sizes = {}):
self.filename = path.split('/')[-1]
self.debug = debug
self.output_name = output_name
self.current_frame = 0
# just temporary
self.big_contour = []
self.centers = []
#check if tiff
if self.filename.split('.')[-1].lower() == 'tif':
self.tiff = tc.opentiff(path)
_,temp_img = self.tiff.retrieve()
temp_img = np.array(temp_img, dtype=np.uint8)
self.images.append(temp_img)
for temp_img in self.tiff:
self.images.append(np.array(temp_img, dtype=np.uint8))
self.img = np.array(self.images[0], dtype=np.uint8)
self.images = []
self.all_frames = len(self.images)
else:
self.img_color = cv2.imread(path)
self.img = self.img_color
self.thresh = self.img
self.org_img = self.img.copy()
self.img_w, self.img_h = self.img.shape[:2] #TODO: check
self.windows_sizes = windows_sizes
self.window = {"max_height": 0, "max_width": 0, "min_height": self.img.shape[:2][0], "min_width": self.img.shape[:2][1]}
import skimage as skimage
import time
RESIZE_FACTOR = 5
DISTANCE_PER_PIXEL = 646.35
#ap = argparse.ArgumentParser()
#ap.add_argument("-i", "--tiff", required=True, help="path to input dataset of images")
#args = vars(ap.parse_args())
file_names = ['28052019_angioE02.tif', '28052019_angioH04.tif']
for file_name in file_names:
tiff = tc.opentiff('videos\\' + file_name)
log_folder_name = 'analysis\\' + file_name + '_imagelog'
if not os.path.exists(log_folder_name):
os.mkdir(log_folder_name)
with open('analysis\\' + file_name + '_result.csv', 'w') as csvfile:
filewriter = csv.writer(csvfile, delimiter=';', lineterminator='\n')
filewriter.writerow([
'Frame', 'number_of_joints', 'number_of_meshes',
'total_meshes_area', 'average_meshes_area', 'number_of_segments',
'total_segments_length'
])
index = 0
#writes a TIFF video into a text file in row order. this works
import tiffcapture as tc
import cv2
from PIL import Image
import numpy
import PIL
import matplotlib.pyplot as plt
tiff = tc.opentiff("Lepton_Capture_2.tiff") #open img
_, first_img = tiff.retrieve()
cv2.namedWindow('video')
imarray = numpy.array(0)
inc = 0
for img in tiff:
#tempimg = cv2.absdiff(first_img, img) # bkgnd sub
plt.imshow(img)
plt.show()
tempimg = img
imarray = numpy.array(tempimg)
np_im = imarray
new_im = Image.fromarray(np_im)
new_im.save("numpy_altered_sample_" + str(inc) + ".png")
f = open("guru99.txt", "w+")
for i in range(0, imarray.shape[0]):
for j in range(0, imarray.shape[1]):
f.write(str(imarray[i, j]) + " ")
f.write("\n")
f.close()
#! /usr/bin/python3
import numpy as np
import cv2
import tiffcapture as tc
import matplotlib.pyplot as plt
def normalize_thermals(img):
cv2.normalize(img, img, 0, 2**16 - 1, cv2.NORM_MINMAX)
return img
tiff = tc.opentiff("lufthavn24feb/20200224_132038/20200224_132425_IR_A.tiff")
vidObj = cv2.VideoCapture(
"lufthavn24feb/20200224_132038/20200224_132425_VIS_A.mov")
n_RGB_frames = int(vidObj.get(cv2.CAP_PROP_FRAME_COUNT))
n_thermal_frames = tiff.length
ratio = n_RGB_frames / n_thermal_frames
_, first_img = tiff.retrieve()
scale_percent = 400 # percent of original size
width = int(first_img.shape[1] * scale_percent / 100)
height = int(first_img.shape[0] * scale_percent / 100)
dim = (width, height)
cv2.namedWindow('thermal_video')
#cv2.namedWindow('RGB_video')
outpath = '{0}/{1}_{2}'.format(path, path.split('/')[-1], args.out)
if not os.path.isdir(outpath):
os.mkdir(outpath)
## iteration on the observation sites (labeled with s + number)
nSite = 1
listfiles=listfiles_all_channel
# process cy5 initial in order to get the positions of patterns,also the size of windows and its area size
pos_all=[]
areas_all=[]
centers_all=[]
pattern_arm_all=[]
for i in xrange(len(listfiles)):
patt = tc.opentiff(path+'/'+listfiles[i])
temp = patt.find_and_read(0)
imObj = utilities.ExtractImage(temp, 6)
img_adapteq = exposure.equalize_adapthist(imObj.smooth, clip_limit=0.03)
img_adapteq /= (np.max(img_adapteq)/255.)
hist,bins = np.histogram(img_adapteq,256,[0,256])
hist2=smooth(hist,40)
histmax = argrelmax(hist2)
ret, thresh=cv2.threshold(np.array(img_adapteq, dtype = np.uint8), (histmax[-1][-1]+255)/2, 255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
thresh[thresh == 0] = 1
thresh[thresh == 255] = 0
selem = disk(5)
thresh = erosion(thresh, selem)
label_image = label(thresh)
rep = regionprops(label_image)
output_dir = 'data/processed/'
visualize = True
verbose = True
## CONFIGURATION ==========
name = filename.split('/')
name = name[len(name) - 1]
name = name.split('.')[0]
if not os.path.isdir(output_dir):
os.mkdir(output_dir)
output_dir_vid = output_dir + name + '/'
if not os.path.isdir(output_dir_vid):
os.mkdir(output_dir_vid)
cap = tc.opentiff(filename)
n_frames = cap.length
## process the first frame
j = 1
if verbose:
print('Processing frame: ' + str(j) + '/' + str(n_frames), end='\r')
# Variable for color to draw optical flow track
color = (0, 255, 0)
# retrieve first frame
ret, first_frame = cap.read()
# Converts frame to grayscale
prev_gray = first_frame
