Hello, I'm trying to run the model but I get the following error

020-06-22 00:20:45.880699: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
[TransNetV2] Using weights from transnetv2-weights/.
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/loader_impl.py", line 98, in parse_saved_model
    saved_model.ParseFromString(file_content)
google.protobuf.message.DecodeError: Error parsing message

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "transnetv2.py", line 188, in <module>
    main()
  File "transnetv2.py", line 160, in main
    model = TransNetV2(args.weights)
  File "transnetv2.py", line 17, in __init__
    self._model = tf.saved_model.load(model_dir)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/load.py", line 578, in load
    return load_internal(export_dir, tags)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/load.py", line 588, in load_internal
    loader_impl.parse_saved_model_with_debug_info(export_dir))
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/loader_impl.py", line 56, in parse_saved_model_with_debug_info
    saved_model = _parse_saved_model(export_dir)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/loader_impl.py", line 101, in parse_saved_model
    raise IOError("Cannot parse file %s: %s." % (path_to_pb, str(e)))
OSError: Cannot parse file b'transnetv2-weights/saved_model.pb': Error parsing message.

Any idea on what could be wrong? thanks

Is there a link where I can manually download the weight, because this weight always times out when my server pulls it. I look forward to hearing from you soon. Thank you very much.

Traceback (most recent call last):
  File "/home/tom/projects/Studium/Studienarbeit/cutting/TransNetV2/inference/transnetv2.py", line 193, in <module>
    main()
  File "/home/tom/projects/Studium/Studienarbeit/cutting/TransNetV2/inference/transnetv2.py", line 173, in main
    model.predict_video(file)
  File "/home/tom/projects/Studium/Studienarbeit/cutting/TransNetV2/inference/transnetv2.py", line 83, in predict_video
    video_stream, err = ffmpeg.input(video_fn).output(
  File "/home/tom/projects/Studium/Studienarbeit/cutting/env/lib/python3.9/site-packages/ffmpeg/_run.py", line 325, in run
    raise Error('ffmpeg', out, err)
ffmpeg._run.Error: ffmpeg error (see stderr output for detail)

I get a ffmpeg error when I run the following command:

python transnetv2.py /mnt/e/Studium/Studienarbeit/Videos/2021/reg/17/c597512d-b37c-11eb-ba8a-ecb6fe06b3b0/highlightsVideo/video/video.mp4 [--visualize]

Thats my ffmpeg:

ffmpeg version 4.2.4-1ubuntu0.1 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 9 (Ubuntu 9.3.0-10ubuntu2)
  configuration: --prefix=/usr --extra-version=1ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --

incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample -

-enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-

libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-

libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --

enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --

enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --

enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 

--enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-

libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared

Is there any problem with my ffmpeg build?

Hi Tomáš,

Your work helps me a lot in understanding your great paper! Thank you so much!

I download the ClipShots training and training transitions datasets, and process them according to https://github.com/soCzech/TransNetV2/blob/master/training/consolidate_datasets.py and https://github.com/soCzech/TransNetV2/blob/master/training/create_dataset.py

I download the ClipShots test dataset and process it accordingly.

I also download the IACC.3 dataset and process it with the type of "train" .

I add the ClipShots training, training transitions and IACC.3 in the "options.trn_files" of https://github.com/soCzech/TransNetV2/blob/master/configs/transnetv2.gin, and add ClipShots test in the "options.tst_files". I also change "options.n_epochs" to 50 as indicated in the paper.

However, I can only obtain F1 of 0.74. Could you please give more training details and instructions on how to reproduce 77.9 on the test set?

What are the meanings of file names in "options.tst_files" and how to generate these files?

I also use the pretrained weights in https://github.com/soCzech/TransNetV2/tree/master/inference/transnetv2-weights to test the ClipShots test dataset by revising "options.restore" and "options.test_only" to True in https://github.com/soCzech/TransNetV2/blob/master/configs/transnetv2.gin. I can only get F1 of 0.2545 and cannot reproduce 77.9.

I appreciate your great help so much!

Wentao

Hi, I tried to run the code as follows.

from transnetv2 import TransNetV2
model = TransNetV2()

For the first time, it shows parse error. I redownload the .pb model. And it show the OpError: not an sstable (bad magic number). Not sure what happened.

I also tried TransNet https://github.com/soCzech/TransNet. It works pretty well. And I like the visualization. I wonder could you please save the TransNet and the weights as a .pb model? Since I want to use it with opencv and c++. Do you have any suggestions that how I can use it with opencv dnn? Suppose I have a video, what should I do to prepare the input for the model? Thank you very much.

Hi, First of all, thank you very much for this work. I have a question that may be a bit silly, but I couldn't find an answer. Indeed, I would like to run the code corresponding to create_train_dataset here , however I can't understand how to fill the mapping_fn parameter : could you tell me what is /path/to/scenes/gt please ? :) I really don't have any idea which file to put...

Hi, in paper, you mentioned that the synthesis data is used and boost performance. But, I didn't find the code to render transitions. Could you please provide the code to render transitions.

after download all the file and trained model/weights manually, I run the transnetv2.py in the inference, but raise an exception: OSError: Cannot parse file b'/path/to/saved_model.pb': Error parsing message. the version of tensorflow is v2.1.0.

and I also run the docker command to build an image flow the readme.md in inference, but after I built the dockerfile successfully, I run the command in the readme.md to test a video, but still raise the same exception.

how can I solve this problem? thanks

Hi Tomas,

Thank you so much for putting this code online. You guys did an excellent job on a model that is still considered a SOTA two years after it was posted!

I'm testing the model on a certain dataset and wanted to ask a few questions:

1. Are you able to share the .h5 file of your training? I want to try to finetune the model with my data and see if it can help me in getting better accuracy compared to training only with my dataset.
2. I'm working on 60fps and sometimes my dissolves tend to get to ~70 frames. What would you suggest I try to change if I want the model to augment with longer transitions? Or generally, would you suggest any chance for higher fps videos and transitions?

I'll really appreciate your help! Happy holidays!

Hi,

Thank you so much for putting this model out. Excellent work! I'm trying to train the model and I stumble upon a problem, that points out to the models.py file When I try to run training.py with the gin file, this is the error message I get:

Traceback (most recent call last): File "C:\videoseg\TransNetV2\training\training.py", line 10, in import models File "C:\videoseg\TransNetV2\training\models.py", line 168, in @gin.configurable(blacklist=["name"]) TypeError: configurable() got an unexpected keyword argument 'blacklist'

Do you have a sense of what could be the problem? Thanks!

The open-source model is saved in pb format, and the training model is saved in hd5 format. How is the hd5 format converted to the pb format? Is it saved directly to pb format during training, or is it converted afterward?