Computer Vision ToolBox

A collection of commonly used tools for general Computer Vision or other Deep Learning projects.

Installation

pip install cvbox

File search and filtering utilities

Utilities to scan files and folders, with options to filter by extension, folders to ignore, etc. Works on both Windows and Linux

from cvbox.search import listfiles, listfiles_gen

dir_to_list = "/path/to/folder/to/search"

# Store all found files in an array
files = listfiles(dir_to_list)
print(files) # Show all the filtered files in dir_to_list


    
# Only include .jpg, .png and .jpeg files
image_paths = listfiles(dir_to_list, extensions=(".jpg",".png","jpeg"))
print(image_paths)

# Return as string instead of pathlib object
image_paths = listfiles(dir_to_list, extensions=(".jpg",".png","jpeg"),return_as_pathlib=False)
print(image_paths)

# Return filenames only
image_names = listfiles(dir_to_list, extensions=(".jpg",".png","jpeg"),return_filename_only=True)
print(image_names)

# Exclude certain extensions (Should not be used together with extensions= argument)
# List all files in dir_to_list that are not .txt or .doc files.
files_exclude_txt = listfiles(dir_to_list,extensions_exclude=(".txt",".doc")) 


# Use generator and process each file lazily. This works on very large folders with 
# large number (>500k) of files
# Just replace listfiles with listfiles_gen (Same function signature as listfiles)
for f in listfiles_gen(dir_to_list):
    # Operate on files lazily
    print(f)

File IO functions - Exporting object state to/from files

Exporting python objects to pickle binary files

from cvbox.fileio import save_pkl, load_pkl

### Quickly serialize/export python objects (can be arrays, dicts, etc) into
### files that can be re-used again (object must be pickle-able)
arr = [1,2,3,4,5]
save_pkl(arr, "arr_output.pkl") # Generates arr_output.pkl in the current directory


arr_loaded = load_pkl("arr_output.pkl") # Restore the array object from file
print(arr_loaded) # [1, 2, 3, 4, 5]

Exporting dictionary objects into JSON text files

from cvbox.fileio import save_json, load_json
dic = [ {"category":"Car","movement": lambda :  "Drive" },
      {"category":"Plane","movement": lambda :  "Fly" }]
save_json("json_output.txt", dic) # Dictionary object is serialized into txt

# Load dictionary from json formatted text
dic_loaded = load_json("json_output.txt")
print(dic_loaded)
# [{'category': 'Car', 'movement': '<not serializable>'},
# {'category': 'Plane', 'movement': '<not serializable>'}]

# Note that non-pickle-able objects such as lambda functions are converted into <not serializable> by default