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vijayvee / video-captioning

This repository contains the code for a video captioning system inspired by Sequence to Sequence -- Video to Text. This system takes as input a video and generates a caption in English describing the video.
MIT License
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Aborted Error #9

Closed sureshkumar96 closed 6 years ago

sureshkumar96 commented 6 years ago

when I run the extract_feats.py code, I got the following error, please resolve this

I0906 07:10:07.085180 26398 layer_factory.hpp:77] Creating layer input I0906 07:10:07.085196 26398 net.cpp:84] Creating Layer input I0906 07:10:07.085204 26398 net.cpp:380] input -> data I0906 07:10:07.085224 26398 net.cpp:122] Setting up input I0906 07:10:07.085232 26398 net.cpp:129] Top shape: 10 3 224 224 (1505280) I0906 07:10:07.085237 26398 net.cpp:137] Memory required for data: 6021120 I0906 07:10:07.085242 26398 layer_factory.hpp:77] Creating layer conv1_1 I0906 07:10:07.085253 26398 net.cpp:84] Creating Layer conv1_1 I0906 07:10:07.085258 26398 net.cpp:406] conv1_1 <- data I0906 07:10:07.085263 26398 net.cpp:380] conv1_1 -> conv1_1 F0906 07:10:07.096971 26398 cudnn_conv_layer.cpp:52] Check failed: error == cudaSuccess (30 vs. 0) unknown error Check failure stack trace: Aborted (core dumped)

vijayvee commented 6 years ago

This is a CUDA error, not a problem with the video-captioning code. Googling the error led me here: https://github.com/NVIDIA/DIGITS/issues/1663

sureshkumar96 commented 6 years ago

Sir, How much time it takes to extract features of all videos. And are the features for only 80 frames(sampled every 10th frame of all the frames.?

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From: Vijay Veerabadran notifications@github.com Sent: Thursday, September 6, 2018 4:47:52 PM To: vijayvee/video-captioning Cc: Optimus_Prime; Author Subject: Re: [vijayvee/video-captioning] Aborted Error (#9)

This is a CUDA error, not a problem with the video-captioning code. Googling the error led me here: NVIDIA/DIGITS#1663https://github.com/NVIDIA/DIGITS/issues/1663

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHubhttps://github.com/vijayvee/video-captioning/issues/9#issuecomment-419057698, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AorZCIXM6mYUISzAPj--fSPYRYkdib7Jks5uYQRggaJpZM4Wctqk.

vijayvee commented 6 years ago

(a) https://github.com/jcjohnson/cnn-benchmarks Here are the benchmarks for various state-of-the-art CNNs including VGG16 that I used for extracting my video features.

The benchmarks say VGG-16 processes a minibatch of 16 frames (of size 224x224) in 128 ms. We have 5 minibatches per video (80=16*5). Each video should hence take about 650 ms on a GTX1080. There were 1970 videos in the dataset => roughly 20 minutes for the whole MSVD dataset I used.

Running time won't be exact but will be in this ^ ballpark, since the preprocessing could be different, and benchmarks were implemented using torch and I use Caffe for feature extraction.

(b) I had computed features for 80 evenly spaced out frames across the video (refer to np.linspace() to know how this works).

sureshkumar96 commented 6 years ago

Sir, then what is frames sampling 1 per 10 frames.

On Sat, Sep 29, 2018 at 12:46 AM Vijay Veerabadran notifications@github.com wrote:

(a) https://github.com/jcjohnson/cnn-benchmarks Here are the benchmarks for various state-of-the-art CNNs including VGG16 that I used for extracting my video features.

The benchmarks say VGG-16 processes minibatch of 16 frames (of size 224x224) in 128 ms. We have 5 minibatches per video (80=16*5). Each video should hence take about 650 ms on a GTX1080.

Running time won't be exact but will be in this ^ ballpark, since the preprocessing could be different, and benchmarks were implemented using torch and I use Caffe for feature extraction.

(b) I had computed features for 80 evenly spaced out frames across the video (refer to np.linspace() to know how this works).

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/vijayvee/video-captioning/issues/9#issuecomment-425538728, or mute the thread https://github.com/notifications/unsubscribe-auth/AorZCHpRplSFOy-ieODf3zeXrnE9Yi87ks5ufnV6gaJpZM4Wctqk .

-- Regards, H.Suresh Kumar, Biological Sciences, IIT Madras, Chennai-600036, 9962427931.

sureshkumar96 commented 6 years ago

---------- Forwarded message --------- From: Suresh kumar hsureshkumar96@gmail.com Date: Tue, Oct 2, 2018 at 1:35 AM Subject: Re: [vijayvee/video-captioning] Aborted Error (#9) To: < reply@reply.github.com

Sir, then what is frames sampling 1 per 10 frames. -pfa for the screenshot of the reference paper that have used.

On Sat, Sep 29, 2018 at 12:46 AM Vijay Veerabadran notifications@github.com wrote:

(a) https://github.com/jcjohnson/cnn-benchmarks Here are the benchmarks for various state-of-the-art CNNs including VGG16 that I used for extracting my video features.

The benchmarks say VGG-16 processes minibatch of 16 frames (of size 224x224) in 128 ms. We have 5 minibatches per video (80=16*5). Each video should hence take about 650 ms on a GTX1080.

Running time won't be exact but will be in this ^ ballpark, since the preprocessing could be different, and benchmarks were implemented using torch and I use Caffe for feature extraction.

(b) I had computed features for 80 evenly spaced out frames across the video (refer to np.linspace() to know how this works).

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/vijayvee/video-captioning/issues/9#issuecomment-425538728, or mute the thread https://github.com/notifications/unsubscribe-auth/AorZCHpRplSFOy-ieODf3zeXrnE9Yi87ks5ufnV6gaJpZM4Wctqk .

-- Regards, H.Suresh Kumar, Biological Sciences, IIT Madras, Chennai-600036, 9962427931.

-- Regards, H.Suresh Kumar, Biological Sciences, IIT Madras, Chennai-600036, 9962427931.