def get_circles(frame, left_crop, right_crop):
red = frame[:, :, 0] - frame[:, :, 2]
red = images.threshold(red, 65)
opened = images.opening(red, (31, 31))
w = opened.shape[1]
im1 = images.crop(opened, left_crop.bbox)
im2 = images.crop(opened, right_crop.bbox)
m1 = list(images.center_of_mass(im1))
m2 = list(images.center_of_mass(im2))
m1[0] += left_crop.bbox.xmin
m1[1] += left_crop.bbox.ymin
m2[0] += right_crop.bbox.xmin
m2[1] += right_crop.bbox.ymin
return np.array([[m1[0], m1[1], 50], [m2[0], m2[1], 50]])
def get_frame(self, crop=True):
frame = self.cam.get_frame()
if self.R != 0:
frame = ndimage.rotate(frame, self.R, reshape=False)
if crop:
frame = images.crop(frame, self.crop)
return frame
def get_circles(self, frame):
red = frame[:, :, 0] - frame[:, :, 2]
red = images.threshold(red, 65)
opened = images.opening(red, (31, 31))
im1 = images.crop(opened, self.left_crop.bbox)
im2 = images.crop(opened, self.right_crop.bbox)
if self.TRACK_LEFT:
m1 = list(images.center_of_mass(im1))
else:
m1 = [im1.shape[1] // 2, im1.shape[0] // 2]
if self.TRACK_RIGHT:
m2 = list(images.center_of_mass(im2))
else:
m2 = [im2.shape[1] // 2, im2.shape[0] // 2]
m1[0] += self.left_crop.bbox.xmin
m1[1] += self.left_crop.bbox.ymin
m2[0] += self.right_crop.bbox.xmin
m2[1] += self.right_crop.bbox.ymin
return np.array([[m1[0], m1[1], 50], [m2[0], m2[1], 50]])
def check(filename):
core_name = os.path.splitext(filename)[0]
vid_name = core_name + '.MP4'
data_name = core_name + '.hdf5'
out_name = core_name + '_check.png'
data = dataframes.DataStore(data_name)
crop = data.metadata['crop']
vid = video.ReadVideo(vid_name)
print(vid_name)
frames = np.arange(4)*vid.num_frames//4
ims = [images.crop(vid.read_frame(f), crop) for f in frames]
circles = [data.get_info(f, ['x', 'y', 'r']) for f in frames]
new_ims = [images.draw_circles(im, c) for im, c in zip(ims, circles)]
out = images.vstack(images.hstack(new_ims[0], new_ims[1]),
images.hstack(new_ims[2], new_ims[3]))
images.save(out, out_name)
from particletracking import dataframes
from labvision import video, images
import numpy as np
import filehandling
file_store = "/media/data/Data/FirstOrder/Hysterisis/FlatPlate/Trial2/0.2_up_1.hdf5"
file_vid = "/media/data/Data/FirstOrder/Hysterisis/FlatPlate/Trial2/0.2_up_1.MP4"
metadata = dataframes.load_metadata(file_store)
vid = video.ReadVideo(file_vid)
box = metadata['crop']
frame = vid.read_frame(vid.num_frames - 1)
frame = images.crop(frame, box)
xmin = 750
xmax = 1250
ymin = 750
ymax = 1250
vertices = np.array([[xmin, ymin], [xmin, ymax], [xmax, ymax], [xmax, ymin]])
frame = images.draw_polygon(frame, vertices, thickness=3)
images.save(
frame,
"/media/data/Data/FirstOrder/Hysterisis/FlatPlate/Trial2/HexagonFigures/box_end.png"
)
images.display(frame)
def get_frame():
frame = cam.get_frame()
if R != 0:
frame = ndimage.rotate(frame, R, reshape=False)
frame = images.crop(frame, crop)
return frame
def crop_then_mask(im):
im = images.crop(im, metadata['crop'])
return mask_from_polygon(im, metadata['boundary'])
def get_frame():
frame = cam.get_frame()
# frame = ndimage.rotate(frame, -120, reshape=False)
frame = images.crop(frame, crop)
return frame
'2': ['16870015', '16870016']
}
files = {r: [direc + d, direc + u] for r, (d, u) in files.items()}
for i, (rate, (down, up)) in enumerate(files.items()):
print(i)
print(rate)
fig, ax = plt.subplots()
ax.set_title(rate)
down_data = dataframes.DataStore(down + '.hdf5')
up_data = dataframes.DataStore(up + '.hdf5')
if i == 0:
up_video = video.ReadVideo(up + '.MP4')
frame = up_video.read_next_frame()
frame = images.crop(frame, up_data.metadata['crop'])
result = images.crop_polygon(frame)
bbox = result.bbox
with open(save_direc + 'bbox.txt', 'w') as f:
f.writelines([
'BBOX xmin, xmax, ymin, ymax',
str(bbox.xmin),
str(bbox.xmax),
str(bbox.ymin),
str(bbox.ymax)
])
frame = images.draw_polygon(
frame,
np.array([[bbox.xmin, bbox.ymin], [bbox.xmin, bbox.ymax],
[bbox.xmax, bbox.ymax], [bbox.xmax, bbox.ymin]],
dtype=np.float32),
def get_frame():
frame = cam.get_frame()
frame = images.crop(frame, crop)
return frame