def get(self, record, random_select = False):
"""
just for one segment
:param record:
:param random_select: train:true test:false
:return:
"""
#read video in this place, if no video here, random select another video
f = open(self.root + record.path, 'rb')
video = f.read()
f.close()
video_frames_num, width, height = utils.video_frame_count(self.root + record.path)
if video_frames_num == -1:
raise RuntimeError("No video stream avilable")
#if video_frames_num < self.new_length:
# print("video{} farmes num is:{}".format(self.root + record.path, video_frames_num))
#opencv ususlly decode more frames, so - 10 here instead of +1
rand_index = randint(0, max(1, video_frames_num - self.new_length - 1))
if video_frames_num > self.new_length:
if random_select:
decoded_images_indexs = np.arange(rand_index, self.new_length + rand_index)
else:
decoded_images_indexs = np.arange(min(rand_index, 10), min(self.new_length + min(rand_index,10), video_frames_num))
else:
decoded_images_indexs = np.arange(0, video_frames_num-1)
#the video may be 224 x 144, need to do resize
#if decoded_images_index is small than new_length, loop until new_length
decoded_images = _load_action_frame_nums_to_4darray(video, decoded_images_indexs, width, height)
if np.shape(decoded_images)[0] < self.new_length:
for i in range(self.new_length - np.shape(decoded_images)[0]):
decoded_images = np.concatenate((decoded_images, np.reshape(decoded_images[i%np.shape(decoded_images)[0], :, :, :], newshape=(1, height, width, 3))), axis=0)
if np.shape(decoded_images)[0] != self.new_length:
raise TypeError("imgs is short than need.!")
process_data = np.asarray(decoded_images, dtype=np.float32)
return process_data, record.label
def get_moco_cv(self, record, random_select = True):
"""
load all video into cv, much slow but accurate
:param record:
:param random_select: train:true test:false
:return:
"""
video_frames_num, width, height = utils.video_frame_count(self.root + record.path)
if video_frames_num == -1:
raise RuntimeError("No video stream avilable")
rand_index = randint(0, max(1, video_frames_num - self.new_length * self.stride - 1))
rand_index2 = randint(0, max(1, video_frames_num - self.new_length * self.stride - 1))
if abs(rand_index - rand_index2) < 4 * self.stride:
if rand_index > rand_index2:
rand_index2 += randint(6*self.stride, max(6*self.stride, video_frames_num-3*self.stride))
else:
rand_index2 += randint(3*self.stride, max(6*self.stride, video_frames_num-9*self.stride))
anchor_indexs = []
negative_indexs = []
for i in range(self.new_length):
anchor_indexs.append((rand_index+i*self.stride)%video_frames_num)
negative_indexs.append((rand_index2+i*self.stride)%video_frames_num)
videodata = skvideo.io.vread(self.root + record.path, num_frames=max(max(anchor_indexs)+1, max(negative_indexs)+1))
anchor = videodata[anchor_indexs, :, :, :]
negative = videodata[negative_indexs,:,:,:]
return anchor, negative, record.label
def get_moco(self, record, random_select = True):
"""
just for one segment
:param record:
:param random_select: train:true test:false
:return:
"""
#read video in this place, if no video here, random select another video
f = open(self.root + record.path, 'rb')
video = f.read()
f.close()
video_frames_num, width, height = utils.video_frame_count(self.root + record.path)
if video_frames_num == -1:
raise RuntimeError("No video stream avilable")
video_frames_num -= 1 # cv2 often more 1 than ffmpeg
rand_index = randint(0, max(1, video_frames_num - self.new_length * self.stride - 1))
if random_select:
decoded_images_indexs = np.arange(rand_index, self.new_length * self.stride + rand_index, self.stride)
else:
decoded_images_indexs = np.arange(min(rand_index, 10), min(self.new_length * self.stride + min(rand_index,10),
video_frames_num), self.stride)
#must be in grow seq
decoded_images_indexs %= video_frames_num
decoded_images_indexs = np.sort(decoded_images_indexs)
for j in range(len(decoded_images_indexs)-1):
if decoded_images_indexs[j] == decoded_images_indexs[j+1]:
decoded_images_indexs[j+1] += 1
# prevent 0,0,0,1,2,3...
if decoded_images_indexs[j] >= decoded_images_indexs[j+1]:
decoded_images_indexs[j+1] = decoded_images_indexs[j] + 1
decoded_images = _load_action_frame_nums_to_4darray(video, np.sort(decoded_images_indexs), width, height)
process_data = np.asarray(decoded_images, dtype=np.float32)
rand_index2 = rand_index
count = 0
# important hyperparameter
thresh = 4
while abs(rand_index - rand_index2) < thresh:
rand_index2 = randint(0, max(1, video_frames_num - self.stride * self.new_length - 1))
count += 1
if count > 3:
rand_index2 = (rand_index2 + randint(max(video_frames_num//8, video_frames_num//3*2))) % video_frames_num
break
if random_select:
decoded_images_indexs2 = np.arange(rand_index2, self.new_length * self.stride + rand_index2, self.stride)
else:
decoded_images_indexs2 = np.arange(min(rand_index2, 10), min(self.new_length + min(rand_index2,10), video_frames_num), self.stride)
decoded_images_indexs2 %= video_frames_num
decoded_images_indexs2 = np.sort(decoded_images_indexs2)
#must be in grow seq
for j in range(len(decoded_images_indexs2)-1):
if decoded_images_indexs2[j] == decoded_images_indexs2[j+1]:
decoded_images_indexs2[j+1] += 1
if decoded_images_indexs2[j] >= decoded_images_indexs2[j+1]:
decoded_images_indexs2[j+1] = decoded_images_indexs2[j] + 1
decoded_images2 = _load_action_frame_nums_to_4darray(video, decoded_images_indexs2, width, height)
process_data2 = np.asarray(decoded_images2, dtype=np.float32)
return process_data, process_data2, record.label