HSV_channel.py

import glob
import os
import sys
from skimage.io import imread
from skimage import color
import numpy as np
from scipy.stats import mode

DIR = "/Users/damoncrockett/Desktop/Seoul_selfies/"

input_paths = [
DIR+"slices_128/",
DIR+"slices_256/",
DIR+"slices_512/"
]

descriptor = "slice"

for input_path in input_paths:
    
    filename = []
    hue = []
    sat = []
    val = []
    hue_med = []
    sat_med = []
    val_med = []
    hue_mode = []
    sat_mode = []
    val_mode = []
    hsd = []
    ssd = []
    vsd = []

    counter = -1
    
    for root, dirs, files in os.walk(input_path):
        for file in files:
            counter +=1

            try:
                img = color.rgb2hsv(imread(root+"/"+file))

                i_hue = np.mean(img[:,:,0])
                hue.append(i_hue)

                i_sat = np.mean(img[:,:,1])
                sat.append(i_sat)

                i_val = np.mean(img[:,:,2])
                val.append(i_val)

                i_hue_med = np.median(img[:,:,0])
                hue_med.append(i_hue_med)

                i_sat_med = np.median(img[:,:,1])
                sat_med.append(i_sat_med)

                i_val_med = np.median(img[:,:,2])
                val_med.append(i_val_med)

                """
                i_hue_mode = float(mode(img[:,:,0],axis=None)[0])
                hue_mode.append(i_hue_mode)

                i_sat_mode = float(mode(img[:,:,1],axis=None)[0])
                sat_mode.append(i_sat_mode)
        
                i_val_mode = float(mode(img[:,:,2],axis=None)[0])
                val_mode.append(i_val_mode)
 
                i_hsd = np.std(img[:,:,0])
                hsd.append(i_hsd)
        
                i_ssd = np.std(img[:,:,1])
                ssd.append(i_ssd)

                i_vsd = np.std(img[:,:,2])
                vsd.append(i_vsd)
                """
                filename.append(root+"/"+file)

                print counter, input_path

            except:
                print counter,file,'error'

    import pandas as pd
    df = pd.DataFrame({'filename':filename,
                       'hue_mean':hue,
                       'sat_mean':sat,
                       'val_mean':val,
                       'hue_med':hue_med,
                       'sat_med':sat_med,
                       'val_med':val_med})
                       #'hue_mode':hue_mode,
                       #'sat_mode':sat_mode,
                       #'val_mode':val_mode,
                       #'hsd':hsd,
                       #'ssd':ssd,
                       #'vsd':vsd})


    df['base'] = df.filename.apply(os.path.basename)
    #df.sort("hue_mode",inplace=True)

    df.to_csv(input_path+descriptor+'_metadata.csv',index=False)
    #df.to_csv(input_path+descriptor+'_metadata.txt',index=False,sep='\t')