loc, 17 "Time taken to transfer files vs number of files \n (10 to 100 files)", 18 ) 19 20 fig = plot_copy_time_vs_num_chart ( 21 res_df, 22 "Time taken to transfer files vs number of files \n (10 to 5000 files)", 23 ) set_visible ( False ) 12 return fig 13 14 15 fig = plot_copy_time_vs_num_chart ( 16 res_df. set_ylabel ( "Time to transfer (seconds)", fontsize = 14 ) 10 ax. set_xlabel ( "Number of Files", fontsize = "large" ) 9 ax. copy_unzip_time / 1000, label = "Copy zip file and unzip" ) 7 ax. copy_files_time / 1000, label = "Copy files" ) 6 ax. suptitle ( title, fontsize = "x-large", fontweight = "bold" ) 4 ax. subplots ( figsize = ( 8, 5 ), facecolor = plt. The transfer times of the zip files, it seems almost flat in comparison to theġ def plot_copy_time_vs_num_chart ( df, title ): 2 fig, ax = plt. Linear fashion as the number of files increases. The following charts shows that the transfer of files individually increases in a Table: Transfer times of increasing number of files using zip compared to transferring individually Number of files Seen that when there are over 4,000 files the use of a zip file to transfer the files This factor increase as the number of files grows and it can be The time to copy the zip file and the unzip time divided by the time to copy theįiles individually.
Transferring files individually increases. That as the number of files increases, the difference between using a zip file and The results confirm what was seen with the initial sample of 10 files. Table: Comparison of directory sizes and zip file size for sample images number of filesĬode to create the sample data from the Cats & Dogs image files.ġ num = 10 2 zip_filename = f "images_.
That it can take a couple of hours for the files to upload to Google Drive. These zip files andĭirectories were uploaded to Google Drive for easy access from Google Colab. That zipping the directories does not reduce the size much. In directories as well as each directory compressed into a zip file. The images were sampled randomlyĪnd split into multiple datasets of the following increasing sizes. Kaggle, but it could be done with any set of images. This experiment was done with some of the images from the dogs-vs-cats data from Significantly improved file transfer times. Very time consuming, even from mapped google drive. In addition, I found that uploading numerous files is Sessions will time out and be shut down and all local variables and loaded data are This is a great free resource, but there are some constraints such as inactive The Jupyter notebooks can be shared,Ĭopied, reviewed and opened on other machines. Google Drive associated with the account. The Colab Jupyter notebooks are saved automatically to the Presents a Jupyter-like notebook interface that is easily accessed through a browser This is an impressive resource that is free to use, it Google released Google Colab in 2017 as an online collaborating tool for machine Transferring the same data as individual files. This article demonstrates that transferring large numbers of imageįiles to Google Colab and decompressing is over 300 times faster than Including the time to decompress the zip file at the destination.įiles can be compressed into a zip file for storage to reduce the amount of disk
The number files to one archive file and this makes file transfer faster, even Image files in the form of jpg are already compressed and compressing them into zipįiles does not significantly reduce the file size further. Compressing multiple files into one archive file allows for faster files transfer.
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