def video_2_frames(VIDEOS_DIR, TARGET_IMAGES_DIR):
files = glob(VIDEOS_DIR + '/' + '*.png')
num = 1
# Remove and make a directory.
if os.path.exists(TARGET_IMAGES_DIR):
shutil.rmtree(TARGET_IMAGES_DIR) # Delete an entire directory tree
if not os.path.exists(TARGET_IMAGES_DIR):
os.makedirs(TARGET_IMAGES_DIR) # Make a directory
for file in files:
e_frame = np.array(Image.open(file))
cube_frame = py360convert.e2c(e_frame,
face_w=256,
mode="bilinear",
cube_format="list")
for i in range(6):
cube_img = Image.fromarray(cube_frame[i])
if not os.path.exists(TARGET_IMAGES_DIR + '/' + str(i)):
os.makedirs(TARGET_IMAGES_DIR + '/' +
str(i)) # Make a directory
cube_img.save(TARGET_IMAGES_DIR + '/' + str(i) + '/' +
os.path.basename(file))
print(
'Save', TARGET_IMAGES_DIR + '/' + str(i) + '/' +
os.path.basename(file))
print('Save ' + str(num) + ' frame')
num += 1
print('Save a diretory')
def equirect_to_cubemap(args, equirect, width, height, cube_side, tempdir):
import py360convert
tempdir = tempdir / 'cubemap'
tempdir.mkdir()
with Image.open(equirect) as equirect_img:
equirect_array = np.array(equirect_img)
# HACK: py360convert flips these faces for some reason; apply corrections
transforms = {
'U': np.flipud,
'R': np.fliplr,
'B': np.fliplr,
}
faces = {}
for face, array in py360convert.e2c(equirect_array,
cube_side,
cube_format='dict').items():
with Image.fromarray(transforms.get(face, lambda x: x)(array)) as img:
faces[face] = tempdir / (face + equirect.suffix)
img.save(faces[face])
cubemap = Cubemap(
px=faces['R'],
nx=faces['L'],
py=faces['U'],
ny=faces['D'],
pz=faces['F'],
nz=faces['B'],
)
return cubemap
def panorama_to_cubemap(panorama_img, face_size=1024, cube_format="dice"):
if not isinstance(panorama_img, np.ndarray):
panorama_img = imageio.imread(panorama_img)
cubemap_img = py360convert.e2c(
e_img=panorama_img, face_w=face_size, cube_format=cube_format
)
return cubemap_img
def saliency(fixmap_input):
(h, w) = fixmap_input.shape
equi_output = np.zeros((h, w, 3))
for shf in range(0, 360, 10):
fixmap_l = fixmap_input[:, 0:int(shf / 360 * w)]
fixmap_r = fixmap_input[:, int(shf / 360 * w):w]
fixmap = np.concatenate((fixmap_r, fixmap_l), axis=1)
fixmap[fixmap > 0] = 255
fixmap = np.expand_dims(fixmap, axis=2)
fixmap = np.concatenate((fixmap, fixmap, fixmap), axis=2)
cube_list = py360convert.e2c(fixmap, cube_format='list')
#cube_dice = py360convert.e2c(fixmap)
#cube_h = py360convert.cube_dice2h(cube_dice) # the inverse is cube_h2dice
#cube_dict = py360convert.cube_h2dict(cube_h) # the inverse is cube_dict2h
cube_list_b = cube_list
for c_key in range(6):
cimg = cube_list[c_key]
#blur = cv2.blur(cimg,(gau_filter, gau_filter))
blur = ndi.gaussian_filter(cimg, gau_filter)
cube_list_b[c_key] = blur
# try:
# imageio.imwrite(dir_location + sound_type[st] + '/' + vid_name + "/frame.png", cimg)
# imageio.imwrite(dir_location + sound_type[st] + '/' + vid_name + "/frame_b.png", blur)
# except:
# pass
#cube_h_b = py360convert.cube_dict2h(cube_dict_b)
#cube_dice_b = py360convert.cube_h2dice(cube_h_b)
equi_b = py360convert.c2e(cube_list, h, w, cube_format='list')
equi_b_l = equi_b[:, 0:w - int(shf / 360 * w), :]
equi_b_r = equi_b[:, w - int(shf / 360 * w):w, :]
equi_b = np.concatenate((equi_b_r, equi_b_l), axis=1)
equi_output = equi_output + equi_b
equi_output = equi_output / 36.0
equi_output = equi_output / equi_output.max()
return equi_output
def get_canvas(frame):
cubes = projector.e2c(frame, cube_format='dict')
F = cubes['F']
D = cubes['D']
B = cubes['B']
L = cubes['L']
R = cubes['R']
U = cubes['U']
FDB = np.concatenate([F, D, np.flipud(B)])
LDR = np.rot90(
np.concatenate([L, np.rot90(D, -1),
np.fliplr(np.rot90(R, -2))], 0), 1)
centre = np.ones((768, 768, 3)).astype(LDR.dtype) * 255
centre[256:-256, :] = LDR
centre[:, 256:-256, :] = FDB
top = np.concatenate([L, F, np.fliplr(R)], 1)
down = np.concatenate([np.rot90(L, -2), np.flipud(B), np.flipud(R)], 1)
left = np.concatenate(
[np.rot90(F, 1),
np.rot90(L, 1),
np.rot90(np.flipud(B), -1)])
right = np.concatenate(
[np.rot90(F, -1),
np.fliplr(np.rot90(R, 1)),
np.fliplr(np.rot90(B))])
pad = 10
canvas = np.ones(
(256 * 2 + 768 + pad * 2, 256 * 2 + 768 + pad * 2, 3)).astype(
centre.dtype) * 255
canvas[256 + pad:256 + pad + 768, 256 + pad:256 + pad + 768] = centre
canvas[:256, 256 + pad:256 + pad + 768] = top
canvas[-256:, 256 + pad:256 + pad + 768] = down
canvas[256 + pad:256 + pad + 768, :256] = left
canvas[256 + pad:256 + pad + 768, -256:] = right
return canvas
import os
for j in [1,2,3,4,5,6,7,8]:
predataset='/home/wang/workspace/21SmartCity/scene'+str(j)
outpath='/home/wang/workspace/cubeImg/scene'+str(j)
if not os.path.exists(outpath):
os.makedirs(outpath)
fileset = os.listdir(predataset)
imgspath=[]
for i in fileset:
if i[-3:] == "jpg" :
imgspath.append(os.path.join(predataset,i))
for i in imgspath:
cube_dice = np.array(Image.open(i))
cubes = py360convert.e2c(cube_dice, 1200)
a = cubes[1200:2400, :1200]
b = cubes[1200:2400, 1200:2400]
c = cubes[1200:2400, 2400:3600]
d = cubes[1200:2400, 3600:4800]
newname = i.split('/')[-1][:-9]
outputImgPath = os.path.join(outpath,newname+'_0.jpg')
plt.imsave(outputImgPath,a)
outputImgPath = os.path.join(outpath,newname+'_1.jpg')
plt.imsave(outputImgPath,b)
outputImgPath = os.path.join(outpath,newname+'_2.jpg')
plt.imsave(outputImgPath,c)
outputImgPath = os.path.join(outpath,newname+'_3.jpg')
plt.imsave(outputImgPath,d)
print(i)
import py360convert import glob import os import PIL from PIL import Image from PIL import ImageFilter import numpy as np import matplotlib.pyplot as plt import numba.cuda as cuda import numba from utils import project, copy sample = './sample/001.png' imgIn = np.array(Image.open(sample)) img_flat = py360convert.e2c(imgIn, face_w=512, mode='bilinear', cube_format='horizon') print(img_flat.shape) plt.imshow(img_flat) plt.show() imgIn_gpu = cuda.to_device (img_flat) imgOut_gpu = cuda.device_array(shape=(1024, 2048, 3), dtype=np.uint8) imgOut_cpu = np.zeros(shape=(1024, 2048, 3), dtype=np.uint8) project[(64, 128), (16, 16)](imgOut_gpu, imgIn_gpu, 1024, 2048, 512) imgOut_gpu.copy_to_host(imgOut_cpu) cuda.synchronize() plt.imshow(imgOut_cpu) plt.show()