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  • Saving mp4 files into csv for training the data

    4 février 2021, par KSp

    I am very new to the computer vision field and I am trying to train my model and as a start of the work, I used a label encoder to label my videos for events I am using. Here I have two events which are accident and no accident.

    


    Folder Structure for the images :

    


    Colab_Notebooks
- accident(all the .jpg frames are here)
- nonaccident(all the .jpg frames are here)


    


    So my data.csv file looks like this and code given below.

    


    data.csv 
image_path,target
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000638.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/nonaccident/nonaccident_0002143.jpg,1.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000372.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000419.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/nonaccident/nonaccident_0001675.jpg,1.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000307.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_00001099.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000940.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000892.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000805.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000232.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000255.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000840.jpg,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000974.jpg,0.0


    


    The code i used for generating data.csv is as shown below :

    


    all_paths = os.listdir('/content/drive/MyDrive/Colab_Notebooks/')

folder_paths = [x for x in all_paths if os.path.isdir('/content/drive/MyDrive/Colab_Notebooks/' + x )]

print(f"Folder paths : {folder_paths}")
print (f"Number of folders: {len(folder_paths)}")
create_labels = ['accident','nonaccident']

data = pd.DataFrame()

image_formats = ['jpg']
labels = []
counter = 0
for i, folder_path in tqdm(enumerate(folder_paths), total = len(folder_paths)):
    if folder_path not in create_labels:
        continue
    image_paths = os.listdir('/content/drive/MyDrive/Colab_Notebooks/' + folder_path)
    label = folder_path

    for image_path in image_paths:
        if image_path.split('.')[-1] in image_formats:
            data.loc[counter,'image_path'] =  f"/content/drive/MyDrive/Colab_Notebooks/{folder_path}/{image_path}"
            labels.append(label)
            counter += 1
labels = np.array(labels)
# one-hot encode the labels
lb = LabelBinarizer()
labels = lb.fit_transform(labels)

#print(labels)

# save as CSV file
data.to_csv('/content/drive/MyDrive/Colab_Notebooks/data.csv', index=False)

# pickle the binarized labels
print('Saving the binarized labels as pickled file')
joblib.dump(lb, '/content/drive/MyDrive/Colab_Notebooks/lb.pkl')

print(data.head(5))


    


    I was able to do this fine because the dataset you see on top is frames which are jpg images. But I would like to do the same for videos.

    


    Colab_Notebooks
- accident(all the .mp4 clips are here)
- nonaccident(all the .mp4 clips are here)

Expected output:
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000638.mp4,0.0
/content/drive/MyDrive/Colab_Notebooks/nonaccident/nonaccident_0002143.mp4,1.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000372.mp4,0.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000419.mp4,0.0
/content/drive/MyDrive/Colab_Notebooks/nonaccident/nonaccident_0001675.mp4,1.0
/content/drive/MyDrive/Colab_Notebooks/accident/accident_0000307.mp4,0.0


    


    Could someone tell me how do I modify the code to read the video clips instead of images ?

    


  • Revision bbffaf627b : Merge "General vp9_encodeframe.c cleanup."

    7 avril 2014, par Dmitry Kovalev

    Changed Paths :
     Modify /vp9/encoder/vp9_encodeframe.c



    Merge "General vp9_encodeframe.c cleanup."

  • Revision 924dc81e74 : Merge "General cleanup in vp9_encodeframe.c."

    10 mars 2014, par Dmitry Kovalev

    Changed Paths :
     Modify /vp9/encoder/vp9_encodeframe.c



    Merge "General cleanup in vp9_encodeframe.c."

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