def display_video_hooks(hook_args):
"""Hooks to display videos at decode time."""
predictions = hook_args.predictions
all_summaries = []
for decode_ind, decode in enumerate(predictions):
target_videos = video_metrics.stack_data_given_key(decode, "targets")
output_videos = video_metrics.stack_data_given_key(decode, "outputs")
input_videos = video_metrics.stack_data_given_key(decode, "inputs")
target_videos = np.asarray(target_videos, dtype=np.uint8)
output_videos = np.asarray(output_videos, dtype=np.uint8)
input_videos = np.asarray(input_videos, dtype=np.uint8)
input_videos = np.concatenate((input_videos, target_videos), axis=1)
output_videos = np.concatenate((input_videos, output_videos), axis=1)
input_summ_vals, _ = common_video.py_gif_summary(
"decode_%d/input" % decode_ind,
input_videos,
max_outputs=10,
fps=10,
return_summary_value=True)
output_summ_vals, _ = common_video.py_gif_summary(
"decode_%d/output" % decode_ind,
output_videos,
max_outputs=10,
fps=10,
return_summary_value=True)
all_summaries.extend(input_summ_vals)
all_summaries.extend(output_summ_vals)
return all_summaries
def display_video_hooks(hook_args):
"""Hooks to display videos at decode time."""
predictions = hook_args.predictions
fps = hook_args.decode_hparams.frames_per_second
border_percent = hook_args.decode_hparams.border_percent
all_summaries = []
for decode_ind, decode in enumerate(predictions):
target_videos = video_metrics.stack_data_given_key(decode, "targets")
output_videos = video_metrics.stack_data_given_key(decode, "outputs")
input_videos = video_metrics.stack_data_given_key(decode, "inputs")
target_videos = np.asarray(target_videos, dtype=np.uint8)
output_videos = np.asarray(output_videos, dtype=np.uint8)
input_videos = np.asarray(input_videos, dtype=np.uint8)
input_videos = create_border(input_videos,
color="blue",
border_percent=border_percent)
target_videos = create_border(target_videos,
color="red",
border_percent=border_percent)
output_videos = create_border(output_videos,
color="red",
border_percent=border_percent)
# Video gif.
all_input = np.concatenate((input_videos, target_videos), axis=1)
all_output = np.concatenate((input_videos, output_videos), axis=1)
input_summ_vals, _ = common_video.py_gif_summary(
"decode_%d/input" % decode_ind,
all_input,
max_outputs=10,
fps=fps,
return_summary_value=True)
output_summ_vals, _ = common_video.py_gif_summary(
"decode_%d/output" % decode_ind,
all_output,
max_outputs=10,
fps=fps,
return_summary_value=True)
all_summaries.extend(input_summ_vals)
all_summaries.extend(output_summ_vals)
# Frame-by-frame summaries
iterable = zip(all_input[:10], all_output[:10])
for ind, (input_video, output_video) in enumerate(iterable):
t, h, w, c = input_video.shape
# Tile vertically
input_frames = np.reshape(input_video, (t * h, w, c))
output_frames = np.reshape(output_video, (t * h, w, c))
# Concat across width.
all_frames = np.concatenate((input_frames, output_frames), axis=1)
tag = "input/output/decode_%d_sample_%d" % (decode_ind, ind)
frame_by_frame_summ = image_utils.image_to_tf_summary_value(
all_frames, tag=tag)
all_summaries.append(frame_by_frame_summ)
return all_summaries
def display_video_hooks(hook_args):
"""Hooks to display videos at decode time."""
predictions = hook_args.predictions
max_outputs = hook_args.decode_hparams.max_display_outputs
max_decodes = hook_args.decode_hparams.max_display_decodes
with tf.Graph().as_default():
_, best_decodes = video_metrics.compute_video_metrics_from_predictions(
predictions, decode_hparams=hook_args.decode_hparams)
all_summaries = []
# Displays decodes corresponding to the best/worst metric,
for metric, metric_decode_inds in best_decodes.items():
curr_metric_inds = metric_decode_inds[:max_outputs]
best_inputs, best_outputs, best_targets = [], [], []
for sample_ind, decode_ind in enumerate(curr_metric_inds):
curr_decode = predictions[decode_ind][sample_ind]
best_inputs.append(curr_decode["inputs"])
best_outputs.append(curr_decode["outputs"])
best_targets.append(curr_decode["targets"])
best_inputs = np.array(best_inputs, dtype=np.uint8)
best_outputs = np.array(best_outputs, dtype=np.uint8)
best_targets = np.array(best_targets, dtype=np.uint8)
summaries = convert_videos_to_summaries(
best_inputs,
best_outputs,
best_targets,
tag=metric,
decode_hparams=hook_args.decode_hparams)
all_summaries.extend(summaries)
# Display random decodes for ten conditioning frames.
for decode_ind, decode in enumerate(predictions[:max_decodes]):
target_videos = video_metrics.stack_data_given_key(decode, "targets")
output_videos = video_metrics.stack_data_given_key(decode, "outputs")
input_videos = video_metrics.stack_data_given_key(decode, "inputs")
target_videos = np.asarray(target_videos, dtype=np.uint8)
output_videos = np.asarray(output_videos, dtype=np.uint8)
input_videos = np.asarray(input_videos, dtype=np.uint8)
summaries = convert_videos_to_summaries(
input_videos,
output_videos,
target_videos,
tag="decode_%d" % decode_ind,
decode_hparams=hook_args.decode_hparams,
display_ground_truth=decode_ind == 0)
all_summaries.extend(summaries)
return all_summaries
