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ইউনপেং লি, ডমিনিক রোবলেক এবং মার্কো তাগলিয়াসাচি। এখান থেকে সেখানে: সরাসরি 3D কনভোলিউশন, 2019 ব্যবহার করে ভিডিওর মধ্যে।
https://arxiv.org/abs/1905.10240
বর্তমান হাবের বৈশিষ্ট্য:
- BAIR রোবট পুশিং ভিডিও এবং KTH অ্যাকশন ভিডিও ডেটাসেটের মডেল রয়েছে (যদিও এই কোল্যাব শুধুমাত্র BAIR ব্যবহার করে)
- হাবে ইতিমধ্যেই BAIR ডেটাসেট উপলব্ধ৷ যাইহোক, কেটিএইচ ভিডিওগুলি ব্যবহারকারীদের নিজেরাই সরবরাহ করতে হবে।
- আপাতত শুধুমাত্র মূল্যায়ন (ভিডিও প্রজন্ম)
- ব্যাচের আকার এবং ফ্রেমের আকার হার্ড কোডেড
সেটআপ
যেহেতু tfds.load('bair_robot_pushing_small', split='test') একটি 30GB সংরক্ষণাগার যে প্রশিক্ষণ তথ্য ধারণ করে ডাউনলোড করবে, আমরা একটি পৃথক সংরক্ষণাগার যে শুধুমাত্র 190MB পরীক্ষা তথ্য ধারণ করে ডাউনলোড করুন। ব্যবহৃত ডেটা সেটটি দ্বারা প্রকাশ করা হয়েছে এই কাগজ এবং 4.0 বাই ক্রিয়েটিভ কমন্স যেমন লাইসেন্সকৃত।
import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import tensorflow_hub as hub
import tensorflow_datasets as tfds
from tensorflow_datasets.core import SplitGenerator
from tensorflow_datasets.video.bair_robot_pushing import BairRobotPushingSmall
import tempfile
import pathlib
TEST_DIR = pathlib.Path(tempfile.mkdtemp()) / "bair_robot_pushing_small/softmotion30_44k/test/"
# Download the test split to $TEST_DIRmkdir -p $TEST_DIRwget -nv https://storage.googleapis.com/download.tensorflow.org/data/bair_test_traj_0_to_255.tfrecords -O $TEST_DIR/traj_0_to_255.tfrecords
2021-11-05 12:44:33 URL:https://storage.googleapis.com/download.tensorflow.org/data/bair_test_traj_0_to_255.tfrecords [189852160/189852160] -> "/tmp/tmpn_2q0lmh/bair_robot_pushing_small/softmotion30_44k/test/traj_0_to_255.tfrecords" [1]
# Since the dataset builder expects the train and test split to be downloaded,
# patch it so it only expects the test data to be available
builder = BairRobotPushingSmall()
test_generator = SplitGenerator(name='test', gen_kwargs={"filedir": str(TEST_DIR)})
builder._split_generators = lambda _: [test_generator]
builder.download_and_prepare()
BAIR: নমপি অ্যারে ইনপুটগুলির উপর ভিত্তি করে ডেমো
# @title Load some example data (BAIR).
batch_size = 16
# If unable to download the dataset automatically due to "not enough disk space", please download manually to Google Drive and
# load using tf.data.TFRecordDataset.
ds = builder.as_dataset(split="test")
test_videos = ds.batch(batch_size)
first_batch = next(iter(test_videos))
input_frames = first_batch['image_aux1'][:, ::15]
input_frames = tf.cast(input_frames, tf.float32)
# @title Visualize loaded videos start and end frames.
print('Test videos shape [batch_size, start/end frame, height, width, num_channels]: ', input_frames.shape)
sns.set_style('white')
plt.figure(figsize=(4, 2*batch_size))
for i in range(batch_size)[:4]:
plt.subplot(batch_size, 2, 1 + 2*i)
plt.imshow(input_frames[i, 0] / 255.0)
plt.title('Video {}: First frame'.format(i))
plt.axis('off')
plt.subplot(batch_size, 2, 2 + 2*i)
plt.imshow(input_frames[i, 1] / 255.0)
plt.title('Video {}: Last frame'.format(i))
plt.axis('off')
Test videos shape [batch_size, start/end frame, height, width, num_channels]: (16, 2, 64, 64, 3)
হাব মডিউল লোড করুন
hub_handle = 'https://tfhub.dev/google/tweening_conv3d_bair/1'
module = hub.load(hub_handle).signatures['default']
WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/weights:0' shape=(4, 4, 4, 3, 64) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/weights:0' shape=(4, 4, 4, 3, 64) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/beta:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/beta:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/gamma:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/gamma:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/weights:0' shape=(4, 4, 4, 64, 128) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/weights:0' shape=(4, 4, 4, 64, 128) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/LayerNorm/beta:0' shape=(128,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/LayerNorm/beta:0' shape=(128,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/weights:0' shape=(4, 4, 4, 3, 64) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/weights:0' shape=(4, 4, 4, 3, 64) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/beta:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/beta:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/gamma:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/gamma:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/weights:0' shape=(4, 4, 4, 64, 128) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/weights:0' shape=(4, 4, 4, 64, 128) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/LayerNorm/beta:0' shape=(128,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/LayerNorm/beta:0' shape=(128,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/weights:0' shape=(4, 4, 4, 3, 64) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/weights:0' shape=(4, 4, 4, 3, 64) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/beta:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/beta:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/gamma:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/gamma:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/weights:0' shape=(4, 4, 4, 64, 128) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/weights:0' shape=(4, 4, 4, 64, 128) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/LayerNorm/beta:0' shape=(128,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/LayerNorm/beta:0' shape=(128,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/weights:0' shape=(4, 4, 4, 3, 64) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/weights:0' shape=(4, 4, 4, 3, 64) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/beta:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/beta:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/gamma:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_0/LayerNorm/gamma:0' shape=(64,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/weights:0' shape=(4, 4, 4, 64, 128) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/weights:0' shape=(4, 4, 4, 64, 128) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/LayerNorm/beta:0' shape=(128,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables(). WARNING:tensorflow:Unable to create a python object for variable <tf.Variable 'video_discriminator/conv_1/LayerNorm/beta:0' shape=(128,) dtype=float32_ref> because it is a reference variable. It may not be visible to training APIs. If this is a problem, consider rebuilding the SavedModel after running tf.compat.v1.enable_resource_variables().
ভিডিও তৈরি করুন এবং দেখান
filled_frames = module(input_frames)['default'] / 255.0
# Show sequences of generated video frames.
# Concatenate start/end frames and the generated filled frames for the new videos.
generated_videos = np.concatenate([input_frames[:, :1] / 255.0, filled_frames, input_frames[:, 1:] / 255.0], axis=1)
for video_id in range(4):
fig = plt.figure(figsize=(10 * 2, 2))
for frame_id in range(1, 16):
ax = fig.add_axes([frame_id * 1 / 16., 0, (frame_id + 1) * 1 / 16., 1],
xmargin=0, ymargin=0)
ax.imshow(generated_videos[video_id, frame_id])
ax.axis('off')
