cvObjParser.py

import cvlib as cv
import cv2
from cvlib.object_detection import draw_bbox
import numpy as np
import sys
import os

# usage: python3 cvObjParser.py [0:no output, 1:output] [image folder path]

# check if want to see image output with first argument (iterate through images with 'q')
check_output = sys.argv[1]

# maps frequency of features
def frequency(features):
    freq = {}
    for feature in features:
        freq[feature] = features.count(feature)
    #for key, value in freq.items():
        #print("% s: % s"%(key, value))
    return freq

# take image folder as argument & extract image paths
folder_path = sys.argv[2]
images = []
for r, d, f in os.walk(folder_path):
    for file in f:
        if '.jpg' in file:
            images.append(os.path.join(r, file))

# extract features from collection of images
img_contrasts = []
features = []
for image in images:
    
    in_img = cv2.imread(image)

    # show original image
    '''
    cv2.imshow('Image', in_img)
    cv2.waitKey()
    '''
 
    # check contrast
    c = cv2.cvtColor(in_img, cv2.COLOR_BGR2YUV)[:,:,0]
    c_min = float(np.min(c))
    c_max = float(np.max(c))
    contrast = (c_max-c_min)/(c_max+c_min)
    img_contrasts.append(round(contrast, 2))
    
    # perform analysis
    bbox, label, conf = cv.detect_common_objects(in_img)
    out_img = draw_bbox(in_img, bbox, label, conf)
    
    # show output image
    '''
    '''
    if check_output == '1':
        cv2.imshow('labeled', out_img)
        cv2.waitKey()
    
    # show features extracted
    for l in label:
        features.append(l)

# filter features into important ones
f = frequency(features)
print('\nImages have the following features & frequencies\n================================================\n')
print(f)

# check if listing furnished
furn_count = 0
filt_feat = ['bench', 'chair', 'couch', 'bed', 'dining table', 'tv', 'clock', 'vase']
for item in filt_feat:
    if item in f:
        furn_count = furn_count+f[item]
print('\nthere are', furn_count, 'pieces of furniture')

# check for plants
plant_count = 0
filt_feat = 'potted plant'
if filt_feat in f:
    plant_count = plant_count+f[filt_feat]
print('there are', plant_count, 'plants')

# check contrast (avg < 0.9 not as nice looking)
avg = 0
for cont in img_contrasts:
    avg = avg+cont
avg = round(avg/len(img_contrasts), 2)
print('image contrast values are', img_contrasts, 'with an average of', avg)

# check if bathroom or kitchen is shown
kitchen = False
filt_feat = ['microwave', 'oven', 'toaster', 'refrigerator']
for item in filt_feat:
    if item in f:
        kitchen = True
if kitchen == True:
    print('Kitchen shown')
else: 
    print('Kitchen not shown')
bathroom = False
if 'toilet' in f:
    bathroom = True
    print('Bathroom shown')
else: 
    print('Bathroom not shown')


# check other features
print('there are', len(images), 'pictures')