import os # Operating System
import sys
import isak
isak.validateArgvMsg("<directory> <dat file>", 3)
directory = str(sys.argv[1])
samp_dir = os.fsencode(directory)
dat_file = open(str(sys.argv[2]), "w")
for im_file in os.listdir(samp_dir) :
im_name = directory + "\\" + os.fsdecode(im_file)
dat_file.write(im_name + " 1 0 0 20 20\n")
dat_file.close()
import os
import cv2
import numpy as np
import re
import sys
import isak # my own library of useful functions
isak.validateArgvMsg("<image directory> <roi file name>", 3)
im_dir_name = str(sys.argv[1])
roi_file = open( str(sys.argv[2]) )
im_dir = os.fsencode(im_dir_name)
for file in os.listdir(im_dir) :
file_name = os.fsdecode(file)
im = cv2.imread(im_dir_name + "\\" + file_name)
for roi in isak.getROIs(roi_file) :
roi = tuple(abs(r) for r in roi)
cropped = isak.cropImage(im, roi)
(h, w, c) = cropped.shape
sf = 1200.0/(max(w,h))
cropped = cv2.resize(cropped, (0,0), fx=sf, fy=sf, interpolation = cv2.INTER_NEAREST)
# Graphical information
isak.drawText(cropped, str(w) + " x " + str(h))
isak.drawCrosshair(cropped)
import os
import cv2
import numpy as np
import re
import sys
import isak
isak.validateArgvMsg("<image directory> <input rois> <output rois>", 4)
samples_dir_name = str(sys.argv[1])
old_rois = str(sys.argv[2])
new_rois = str(sys.argv[3])
beta_rois_file = open(new_rois, "w")
rois_file = open(old_rois, "r")
samples_dir = os.fsencode(samples_dir_name)
files = os.listdir(samples_dir)
num_images = len(files)
img_ctr = 1
for file in files:
file_name = os.fsdecode(file)
im = cv2.imread(samples_dir_name + "\\" + file_name)
beta_rois_file.write(file_name + " : ")
ctr = 0
for roi in isak.getROIs(rois_file):
import os
import cv2
import numpy as np
import sys
import isak
isak.validateArgvMsg("<samples directory>", 2)
samples_dir_name = str(sys.argv[1])
samples_dir = os.fsencode(samples_dir_name)
files = os.listdir(samples_dir)
num_files = len(files)
ctr = 0
for file in files :
file_name = os.fsdecode(file)
im = cv2.imread(samples_dir_name + "\\" + file_name)
sf = 16.0
im = cv2.resize(im, (0,0), fx=sf, fy=sf, interpolation = cv2.INTER_NEAREST)
isak.drawText(im, str(ctr) + "/" + str(num_files) )
cv2.imshow("test", im)
key = cv2.waitKey()
if (key == ord('x')) : # then delete that sample
os.remove(samples_dir_name + "\\" + file_name)
g_filt = g / grayscale
g_filt = unitAdjust(g_filt)
g_filt *= g_filt
# out
out = r_filt - b_filt - g_filt + 2.0
out = unitAdjust(out)
out *= out
# out *= out
# out *= out
# out = r
out = 255.0 * out
return out.astype(np.uint8)
isak.validateArgvMsg("<cascade xml file> <name of image directory>", 3)
cascade_xml = str(sys.argv[1])
img_dir_name = str(sys.argv[2])
img_dir = os.fsencode(img_dir_name)
for img_file in os.listdir(img_dir):
file_name = os.fsdecode(img_file)
img = cv2.imread(img_dir_name + "\\" + file_name)
gray = preprocess(img)
cascade = cv2.CascadeClassifier(cascade_xml)
centers = myDetect(gray, cascade)
rects = detect(gray, cascade)