def main():
import sys
try:
fn = sys.argv[1]
except:
fn = 'example_wood.jpg'
img = cv.imread(cv.samples.findFile(fn))
if img is None:
print('Failed to load image file:', fn)
sys.exit(1)
img_original = img.copy()
cv.imshow('original', img_original)
img_mark = img.copy()
mark = np.zeros(img.shape[:2], np.uint8)
sketch = Sketcher('img', [img_mark, mark], lambda: ((255, 255, 255), 255))
while True:
ch = cv.waitKey()
if ch == 27:
break
if ch == ord(' '):
res = cv.inpaint(img_mark, mark, 3, cv.INPAINT_TELEA)
cv.imshow('inpaint', res)
if ch == ord('r'):
img_mark[:] = img
mark[:] = 0
sketch.show()
print('Done')
def __init__(self, fn):
self.img = cv2.imread(fn)
h, w = self.img.shape[:2]
self.markers = np.zeros((h, w), np.int32)
self.markers_vis = self.img.copy()
self.cur_marker = 1
self.colors = np.int32( list(np.ndindex(2, 2, 2)) ) * 255
self.auto_update = True
self.sketch = Sketcher('img', [self.markers_vis, self.markers], self.get_colors)
def __init__(self, fn):
self.img = cv.imread(fn)
if self.img is None:
raise Exception('Failed to load image file: %s' % fn)
h, w = self.img.shape[:2]
self.markers = np.zeros((h, w), np.int32)
self.markers_vis = self.img.copy()
self.cur_marker = 1
self.colors = np.int32( list(np.ndindex(2, 2, 2)) ) * 255
self.auto_update = True
self.sketch = Sketcher('img', [self.markers_vis, self.markers], self.get_colors)
def __init__(self, fn):
#self.img = cv.imread(fn)
self.img = fn
if self.img is None:
raise Exception('Failed to load image file: %s' % fn)
h, w = self.img.shape[:2]
self.markers = np.zeros((h, w), np.int32)
self.markers_vis = self.img.copy()
self.cur_marker = 1
self.colors = np.int32(list(np.ndindex(2, 2, 2))) * 255
self.thresh_value = 50
self.thresh_max = None
self.auto_update = True
self.preprocess(0)
self.sketch = Sketcher('img', [self.markers_vis, self.markers],
self.get_colors)
self.boundary_points = []
def main():
canvas = numpy.ones((h + tah, w))
cv2.line(canvas, (0, tah - 1), (w, tah - 1), (0, 0, 0), 1)
cv2.line(canvas, (145, 0), (145, tah - 1), (.5, 255, 255), 1)
font = cv2.FONT_HERSHEY_PLAIN
font2 = cv2.FONT_HERSHEY_TRIPLEX
text1 = "Press 'C' to clear"
cv2.putText(canvas, text1, (5, 10), font, 0.9, (0.5, 255, 0), 1)
text2 = "Press 'T' to test"
cv2.putText(canvas, text2, (5, 22), font, 0.9, (0.5, 255, 0), 1)
img = canvas.copy()
sketch = Sketcher('Draw', [img], lambda: ((0, 255, 0), 255))
while (True):
if (cv2.waitKey() == ord('c')):
print("Clear")
img[:] = canvas
sketch.show()
if (cv2.waitKey() == ord('t')):
process(img)
output = str(random.randint(0, 10))
cv2.putText(img, output, (162, 22), font2, 1, (0, 255, 0), 1)
sketch.show()
print("Test")
if (cv2.getWindowProperty('Draw', 0) == -1) or (cv2.waitKey() == 27):
break
cv2.destroyAllWindows()
import numpy as np
import cv2
from common import Sketcher
if __name__ == '__main__':
import sys
try:
fn = sys.argv[1]
except:
fn = '../cpp/fruits.jpg'
print __doc__
img = cv2.imread(fn)
img_mark = img.copy()
mark = np.zeros(img.shape[:2], np.uint8)
sketch = Sketcher('img', [img_mark, mark], lambda: ((255, 255, 255), 255))
while True:
ch = 0xFF & cv2.waitKey()
if ch == 27:
break
if ch == ord(' '):
res = cv2.inpaint(img_mark, mark, 3, cv2.INPAINT_TELEA)
cv2.imshow('inpaint', res)
if ch == ord('r'):
img_mark[:] = img
mark[:] = 0
sketch.show()
cv2.destroyAllWindows()
def main():
"""
Main method of the program.
"""
# Pull system arguments
try:
fn = sys.argv[1]
except:
fn = INPUT_IMAGE
# Load the image and store into a variable
#image = cv2.imread(cv2.samples.findFile(fn))
image = cv2.imread('mango_img_752.png')
if image is None:
print('Failed to load image file:', fn)
sys.exit(1)
# Create an image for sketching the mask
image_mark = image.copy()
sketch = Sketcher('Image', [image_mark], lambda: ((255, 255, 255), 255))
# Sketch a mask
while True:
ch = cv2.waitKey()
if ch == 27: # ESC - exit
break
if ch == ord('r'): # r - mask the image
break
if ch == ord(' '): # SPACE - reset the inpainting mask
image_mark[:] = image
sketch.show()
# define range of white color in HSV
lower_white = np.array([0, 0, 255])
upper_white = np.array([255, 255, 255])
# Create the mask
mask = cv2.inRange(image_mark, lower_white, upper_white)
# Create the inverted mask
mask_inv = cv2.bitwise_not(mask)
# Convert to grayscale image
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Extract the dimensions of the original image
rows, cols, channels = image.shape
#print(image.shape)
image = image[0:rows, 0:cols]
# Bitwise-OR mask and original image
colored_portion = cv2.bitwise_or(image, image, mask=mask)
colored_portion = colored_portion[0:rows, 0:cols]
cv2.imshow('Mask', colored_portion)
# Bitwise-OR inverse mask and grayscale image
gray_portion = cv2.bitwise_or(gray, gray, mask=mask_inv)
gray_portion = np.stack((gray_portion, ) * 3, axis=-1)
# Combine the two images
output = colored_portion + gray_portion
# Save the image
#cv2.imwrite(OUTPUT_IMAGE, output)
# Create a table showing input image, mask, and output
mask = np.stack((mask, ) * 3, axis=-1)
table_of_images = np.concatenate((image, mask, output), axis=1)
#cv2.imwrite(TABLE_IMAGE, table_of_images)
# Display images, used for debugging
'''cv2.imshow('Original Image', image)
cv2.imshow('Sketched Mask', image_mark)
cv2.imshow('Mask', mask)
cv2.imshow('Output Image', output)'''
#cv2.imshow('Table of Images', table_of_images)
cv2.waitKey(0) # Wait for a keyboard event
def main():
try:
fn = sys.argv[1]
except:
fn = INPUT_IMAGE
image = cv2.imread(cv2.samples.findFile(fn))
# Resim bulunamazsa program bozulmasın
if image is None:
print('Failed to load image file:', fn)
sys.exit(1)
# Common dosyamızdan örnek oluşturalım
image_mark = image.copy()
sketch = Sketcher('Image', [image_mark], lambda: ((255, 255, 255), 255))
# Kullanıcı Komut alanı
while True:
ch = cv2.waitKey()
if ch == 27: # ESC - exit
break
if ch == ord('r'): # r - mask the image
break
if ch == ord(' '): # SPACE - reset the inpainting mask
image_mark[:] = image
sketch.show()
# Ten rengine göre uygun renk aralığı ataması
lower_white = np.array([50, 50, 50])
upper_white = np.array([255, 255, 255])
mask = cv2.inRange(image_mark, lower_white, upper_white)
# Maskeleme işlemi
mask_inv = cv2.bitwise_not(mask)
# Renk dönüşüm alanı
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
rows, cols, channels = image.shape
image = image[0:rows, 0:cols]
colored_portion = cv2.bitwise_or(image, image, mask=mask)
colored_portion = colored_portion[0:rows, 0:cols]
gray_portion = cv2.bitwise_or(gray, gray, mask=mask_inv)
gray_portion = np.stack((gray_portion, ) * 3, axis=-1)
# Çıktı oluşturulan alan
output = colored_portion + gray_portion
# Çıktıyı kayıt edelim
cv2.imwrite(OUTPUT_IMAGE, output)
# Fotoğrafın ilk ve son halini tabloya dönüştürelim
mask = np.stack((mask, ) * 3, axis=-1)
table_of_images = np.concatenate((image, mask), axis=1)
cv2.imwrite(TABLE_IMAGE, table_of_images)
# Kullanıcıya gösterelim
#cv2.imshow('Original Image', image)
#cv2.imshow('Output Image', output)
cv2.imshow('Table of Images', table_of_images)
cv2.waitKey(0)
def main():
"""
Main method of the program.
"""
imgList = []
for img in all_files:
imgList.append(img)
print(len(imgList))
INPUT_IMAGE = imgList[14]
IMAGE_NAME = INPUT_IMAGE[:INPUT_IMAGE.index(".")]
OUTPUT_IMAGE = IMAGE_NAME + "_output.png"
try:
fn = sys.argv[1]
except:
fn = INPUT_IMAGE
image = cv2.imread(INPUT_IMAGE)
#cv2.imshow('Mask', image)
#print(img)
if image is None:
print('Failed to load image file:', fn)
sys.exit(1)
# Create an image for sketching the mask
image_mark = image.copy()
sketch = Sketcher('Image', [image_mark], lambda: ((255, 255, 255), 255))
while True:
ch = cv2.waitKey()
if ch == 27: # ESC - exit
cv2.destroyAllWindows()
break
if ch == ord('r'): # r - mask the image
break
if ch == ord(' '): # SPACE - reset the inpainting mask
image_mark[:] = image
sketch.show()
# define range of white color in HSV
lower_white = np.array([0, 0, 255])
upper_white = np.array([255, 255, 255])
# Create the mask
mask = cv2.inRange(image_mark, lower_white, upper_white)
# Create the inverted mask
mask_inv = cv2.bitwise_not(mask)
# Convert to grayscale image
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Extract the dimensions of the original image
rows, cols, channels = image.shape
#print(image.shape)
image = image[0:rows, 0:cols]
# Bitwise-OR mask and original image
colored_portion = cv2.bitwise_or(image, image, mask=mask)
colored_portion = colored_portion[0:rows, 0:cols]
os.chdir(
"/Users/pavankumar/Documents/Processed Datasets/scripts/msk_unripen/")
#out = os.path.join(os.getcwd() , '/MaskedImages/').join(OUTPUT_IMAGE)
print(OUTPUT_IMAGE)
cv2.imwrite(OUTPUT_IMAGE, colored_portion)
cv2.waitKey(0) # Wait for a keyboard event
def draw(h, w, tah):
canvas = np.ones((h + tah, w), dtype=np.float32)
cv2.line(canvas, (0, tah - 1), (w, tah - 1), (0, 0, 0), 1)
cv2.line(canvas, (201, 0), (201, h + tah), (.5, 255, 255), 1)
cv2.line(canvas, (402, 0), (402, h + tah), (.5, 255, 255), 1)
font = cv2.FONT_HERSHEY_PLAIN
font2 = cv2.FONT_HERSHEY_TRIPLEX
font3 = cv2.FONT_HERSHEY_SIMPLEX
font4 = cv2.FONT_HERSHEY_DUPLEX
#left box
text1 = "Press 'C' to clear"
cv2.putText(canvas, text1, (20, 10), font, 0.9, (0.5, 255, 0), 1)
text2 = "Press 'E' to evaluate"
cv2.putText(canvas, text2, (20, 22), font, 0.9, (0.5, 255, 0), 1)
#middle box
text3 = "Prediction"
cv2.putText(canvas, text3, (240, 22), font3, .7, (0, 255, 0), 1)
#right box
text4 = "Confidence"
cv2.putText(canvas, text4, (440, 22), font3, .7, (0, 255, 0), 1)
img = canvas.copy()
sketch = Sketcher(name, [img], lambda: ((0, 255, 0), 255))
while (True):
if cv2.waitKey(0) == ord('c'):
# clear the screen
print("Clear")
img[:] = canvas
sketch.show()
if cv2.waitKey(0) == ord('e'):
# evaluate drawing
# remove previous results from screen
cv2.rectangle(img, (202, tah), (400, h + tah), (255, 255, 255), -1)
cv2.rectangle(img, (404, tah), (600, h + tah), (255, 255, 255), -1)
img2 = process(
img) #call process img to apply filtering and edge detection
#convert image into tensor input
to_eval = tf.estimator.inputs.numpy_input_fn(x={"x": img2},
y=None,
shuffle=False)
# evaluate input image, Returns np.array
output1 = classifier.predict(input_fn=to_eval)
output2 = classifier.predict(input_fn=to_eval)
#extract prediction class and probabilities from classfier
output_classes = [c['classes'] for c in output1]
output_prob = [p['probabilities'] for p in output2]
#sort probabilities
probs = output_prob[0]
vals = []
for i in range(0, len(probs)):
vals.append((i, probs[i]))
sorted_probs = sorted(vals, key=lambda x: x[1])
#determine confidency level
if sorted_probs[-1][1] >= 0.9:
conf = 'Very Confident'
elif sorted_probs[-1][1] < 0.9 and sorted_probs[-1][1] >= 0.8:
conf = 'Confident'
elif sorted_probs[-1][1] < 0.8 and sorted_probs[-1][1] >= 0.65:
conf = 'Somewhat Confident'
elif sorted_probs[-1][1] < 0.65:
conf = 'Not Confident'
# print evaluation confidence
prob2 = str(sorted_probs[-2][0]) + ' = ' + str(sorted_probs[-2][1])
cv2.putText(img, conf, (430, 115), font3, .6, (0, 255, 0), 1)
# print prediction
output = str(output_classes)
cv2.putText(img, str(output[1]), (250, 150), font4, 4, (0, 255, 0),
3)
sketch.show()
print("Eval")
if (cv2.getWindowProperty(name, 0) == -1) or (cv2.waitKey() == 27):
break
cv2.destroyAllWindows()
