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 main():
import sys
try:
fn = sys.argv[1]
except:
fn = 'fruits.jpg'
img = cv.imread(cv.samples.findFile(fn))
if img is None:
print('Failed to load image file:', fn)
sys.exit(1)
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)
class App:
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 get_colors(self):
return list(map(int, self.colors[self.cur_marker])), self.cur_marker
def watershed(self):
m = self.markers.copy()
cv.watershed(self.img, m)
cv.imshow('watershed1', self.img)
overlay = self.colors[np.maximum(m, 0)]
vis = cv.addWeighted(self.img,
0.5,
overlay,
0.5,
0.0,
dtype=cv.CV_8UC3)
cv.imshow('watershed2', vis)
def run(self):
while cv.getWindowProperty('img', 0) != -1 or cv.getWindowProperty(
'watershed', 0) != -1:
ch = cv.waitKey(50)
if ch == 27:
break
if ch >= ord('1') and ch <= ord('7'):
self.cur_marker = ch - ord('0')
print('marker: ', self.cur_marker)
if ch == ord(' ') or (self.sketch.dirty and self.auto_update):
self.watershed()
self.sketch.dirty = False
if ch in [ord('a'), ord('A')]:
self.auto_update = not self.auto_update
print('auto_update if', ['off', 'on'][self.auto_update])
if ch in [ord('r'), ord('R')]:
self.markers[:] = 0
self.markers_vis[:] = self.img
self.sketch.show()
cv.destroyAllWindows()
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)
class App:
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 get_colors(self):
return map(int, self.colors[self.cur_marker]), self.cur_marker
def watershed(self):
m = self.markers.copy()
cv2.watershed(self.img, m)
overlay = self.colors[np.maximum(m, 0)]
vis = cv2.addWeighted(self.img,
0.5,
overlay,
0.5,
0.0,
dtype=cv2.CV_8UC3)
cv2.imshow('watershed', vis)
def run(self):
while True:
ch = 0xFF & cv2.waitKey(50)
if ch == 27:
break
if ch >= ord('1') and ch <= ord('7'):
self.cur_marker = ch - ord('0')
print 'marker: ', self.cur_marker
if ch == ord(' ') or (self.sketch.dirty and self.auto_update):
self.watershed()
self.sketch.dirty = False
if ch in [ord('a'), ord('A')]:
self.auto_update = not self.auto_update
print 'auto_update if', ['off', 'on'][self.auto_update]
if ch in [ord('r'), ord('R')]:
self.markers[:] = 0
self.markers_vis[:] = self.img
self.sketch.show()
cv2.destroyAllWindows()
class App:
def __init__(self, fn):
self.img = cv2.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 get_colors(self):
return list(map(int, self.colors[self.cur_marker])), self.cur_marker
def watershed(self):
m = self.markers.copy()
cv2.watershed(self.img, m)
overlay = self.colors[np.maximum(m, 0)]
vis = cv2.addWeighted(self.img, 0.5, overlay, 0.5, 0.0, dtype=cv2.CV_8UC3)
cv2.imshow('watershed', vis)
def run(self):
while True:
ch = 0xFF & cv2.waitKey(50)
if ch == 27:
break
if ch >= ord('1') and ch <= ord('7'):
self.cur_marker = ch - ord('0')
print('marker: ', self.cur_marker)
if ch == ord(' ') or (self.sketch.dirty and self.auto_update):
self.watershed()
self.sketch.dirty = False
if ch in [ord('a'), ord('A')]:
self.auto_update = not self.auto_update
print('auto_update if', ['off', 'on'][self.auto_update])
if ch in [ord('r'), ord('R')]:
self.markers[:] = 0
self.markers_vis[:] = self.img
self.sketch.show()
cv2.destroyAllWindows()
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, prefix, dryRun):
h, w = 300, 300
img = np.zeros((h, w, 3), np.uint8)
img[:,:] = (255, 255, 255)
self.brush = Brush("Brush")
self.sketcher = Sketcher("Dataset Creator", img, self.brush)
self.__folders = OCR.generateFolderList(OCR.DIGITS | OCR.LETTERS | OCR.SYMBOLS)
self.__prefix = prefix
self.__lastFile = None
self.__dryRun = dryRun
class App:
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 get_colors(self):
return map(int, self.colors[self.cur_marker]), self.cur_marker
def watershed(self):
m = self.markers.copy()
cv2.watershed(self.img, m)
overlay = self.colors[np.maximum(m, 0)]
vis = cv2.addWeighted(self.img, 0.5, overlay, 0.5, 0.0, dtype=cv2.CV_8UC3)
cv2.imshow("watershed", vis)
def run(self):
while True:
ch = 0xFF & cv2.waitKey(50)
if ch == 27:
break
if ch >= ord("1") and ch <= ord("7"):
self.cur_marker = ch - ord("0")
print "marker: ", self.cur_marker
if ch == ord(" ") or (self.sketch.dirty and self.auto_update):
self.watershed()
self.sketch.dirty = False
if ch in [ord("a"), ord("A")]:
self.auto_update = not self.auto_update
print "auto_update if", ["off", "on"][self.auto_update]
if ch in [ord("r"), ord("R")]:
self.markers[:] = 0
self.markers_vis[:] = self.img
self.sketch.show()
cv2.destroyAllWindows()
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 __init__(self, fn):
self.img = cv2.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)
class DatasetCreator:
ESC = 27
DEL = 127
RET = 13
KEY_UP = 0
KEY_DOWN = 1
EXT = ".bmp"
FINAL_SIZE = 50
def __init__(self, prefix, dryRun):
h, w = 300, 300
img = np.zeros((h, w, 3), np.uint8)
img[:,:] = (255, 255, 255)
self.brush = Brush("Brush")
self.sketcher = Sketcher("Dataset Creator", img, self.brush)
self.__folders = OCR.generateFolderList(OCR.DIGITS | OCR.LETTERS | OCR.SYMBOLS)
self.__prefix = prefix
self.__lastFile = None
self.__dryRun = dryRun
def run(self):
while True:
k = cv2.waitKey(0) & 0xFF
if k == self.ESC:
break
elif k == self.RET:
self.sketcher.reset()
self.sketcher.show()
elif k == self.KEY_UP:
self.brush.brushSize += 1
elif k == self.KEY_DOWN:
self.brush.brushSize -= 1
elif k == self.DEL and not self.__dryRun:
if self.__lastFile:
os.remove(self.__lastFile)
self.__lastFile = None
print path + " Removed"
elif chr(k) in self.__folders:
folder = self.__folders[chr(k)]
path = common.generateFilename(folder, self.__prefix, self.EXT)
item = self.sketcher.sketch.copy()
item = cv2.resize(item, (self.FINAL_SIZE, self.FINAL_SIZE))
cv2.imshow("Generated Dataset item", item)
self.sketcher.reset()
self.__lastFile = path
if not self.__dryRun:
cv2.imwrite(path, item)
print path + " Written"
else:
print path + " Preview"
def __init__(self, model, filenames, flags, pattern):
self.ocr = OCR()
self.ocr.loadModel(model, OCR.MODEL_ANN, flags)
if filenames:
counter = {}
for filename in filenames:
ch = self.ocr.charFromFile(filename)
if pattern:
label = self.__exec(pattern, filename)
if label in counter:
predicted, total = counter[label]
counter[label] = (predicted + int(label == ch), total + 1)
else:
counter[label] = (int(label == ch), 1)
print "%s in %s" % (ch, filename)
if pattern:
self.__analyze(counter)
else:
h, w = 200, 200
img = np.zeros((h, w, 3), np.uint8)
img[:,:] = (255, 255, 255)
self.brush = Brush("Brush")
self.sketcher = Sketcher('Test OCR', img, self.brush)
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()
#cv2.imshow('im_FG',im_FG)
cv2.imshow('颜色捕捉',im_all)
cv2.imshow('123',im_all)
#cv2.imshow('456',mixed_clone)
cn=cv2.waitKey(50)
if cn==ord(' '):
d=c+1
if c==d:
print ('0')
cn=cv2.waitKey(30)
now = datetime.datetime.now()
#print ("yes")
im_name1=(now.strftime('%Y-%m-%d_%H%M%S')+'.jpg')
img_mark = im_all.copy()
mark = np.zeros(im_all.shape[:2], np.uint8)
sketch = Sketcher('可编辑', [img_mark, mark], lambda : ((255, 255, 255), 255))
while(cn!=27):
cn=cv2.waitKey(10)
res = cv2.inpaint(img_mark, mark, 3, cv2.INPAINT_TELEA)
cv2.imshow('可编辑',res)
print cn
print 'yes'
#
cv2.imwrite('images/'+im_name1,res)
cv2.imshow('可编辑',res)
cv2.waitKey(2000)
cv2.destroyWindow('可编辑')
print ('done')
class App:
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 change_thresh(self):
self.thresh_value += 10
if self.thresh_value > self.thresh_max:
self.thresh_value = 10
# 经过一系列图像处理得到一些前景和背景信息
def preprocess(self, flag=0):
gray = cv.cvtColor(self.img, cv.COLOR_BGR2GRAY)
# cv.imshow("gray", gray)
# ret:返回的阈值, thresh:返回的二值化图像
if flag == 0:
ret, thresh = cv.threshold(gray, 0, 255,
cv.THRESH_BINARY + cv.THRESH_OTSU)
self.thresh_max = ret
else:
ret, thresh = cv.threshold(gray, self.thresh_value, 255,
cv.THRESH_BINARY)
# print("ret:", ret)
# cv.imshow("thresh", thresh)
# noise removal
kernel = np.ones((3, 3), np.uint8)
opening = cv.morphologyEx(thresh, cv.MORPH_OPEN, kernel, iterations=2)
# cv.imshow("opening", opening)
# sure background area
sure_bg = cv.dilate(opening, kernel, iterations=30)
# cv.imshow("sure_bg", sure_bg)
# Finding sure foreground area
# distanceTransform用于计算每个非零像素距离与其最近的零点像素之间的距离，
# 输出的是保存每一个非零点与最近零点的距离信息
dist_transform = cv.distanceTransform(opening, cv.DIST_L2, 5)
normalized_img = np.zeros(dist_transform.shape)
normalized_img = cv.normalize(dist_transform, normalized_img, 0, 255,
cv.NORM_MINMAX)
normalized_img = np.uint8(normalized_img)
# cv.imshow("normalize_img", normalized_img)
# self.write_matrix_to_file(normalized_img)
ret, sure_fg = cv.threshold(dist_transform, 0.7 * dist_transform.max(),
255, 0)
sure_fg = np.uint8(sure_fg)
# cv.imshow("sure_fg", sure_fg)
# Finding unknown region
# unknown = cv.subtract(sure_bg, sure_fg)
# Marker labelling
# ret：一共有多少个区域,前景数+1(背景)
# markers：为区域编号的矩阵,背景为0,前景依次为1,2,3
ret, markers = cv.connectedComponents(sure_fg)
# 前景标记为1，背景标记为2
self.markers[markers[:, :] == 1] = 1
self.markers[sure_bg[:, :] == 0] = 2
# self.write_matrix_to_file(self.markers)
overlay = self.colors[np.maximum(self.markers, 0)]
alpha = np.zeros(overlay.shape)
for a in range(3):
# 这里im2[:,:,a]!=0生成一个bool型矩阵掩码
alpha[overlay[:, :, a] != 0] = 0.5
# self.markers_vis = cv.addWeighted(self.markers_vis, 0.5, overlay, 0.5, 0.0, dtype=cv.CV_8UC3)
self.markers_vis[:] = overlay * alpha + self.markers_vis * (1 - alpha)
self.markers_vis[:] = np.uint8(self.markers_vis)
def reset(self):
self.markers[:] = 0
self.markers_vis[:] = self.img
def get_colors(self):
return list(map(int, self.colors[self.cur_marker])), self.cur_marker
def watershed(self):
m = self.markers.copy() # m.shape = (h, w)
self.write_matrix_to_file(m)
cv.watershed(self.img, m)
overlay = self.colors[np.maximum(m, 0)]
self.vis = cv.addWeighted(self.img,
0.5,
overlay,
0.5,
0.0,
dtype=cv.CV_8UC3)
# cv.imshow('watershed', self.vis)
ol = overlay.astype(np.uint8)
mask_bool = ol[:, :, 2] == 255
nonb = mask_bool.nonzero()
all_points_y = nonb[0].tolist()
all_points_x = nonb[1].tolist()
self.boundary_points.clear()
self.boundary_points.append(all_points_x)
self.boundary_points.append(all_points_y)
def start(self):
self.watershed()
return self.vis, self.boundary_points
def run(self):
self.watershed()
while cv.getWindowProperty('img', 0) != -1 or cv.getWindowProperty(
'watershed', 0) != -1:
ch = cv.waitKey(50)
if ch == 27:
break
if ch >= ord('1') and ch <= ord('7'):
self.cur_marker = ch - ord('0')
print('marker: ', self.cur_marker)
if self.sketch.dirty and self.auto_update:
self.watershed()
self.sketch.dirty = False
if ch in [ord('a'), ord('A')]:
self.auto_update = not self.auto_update
print('auto_update if', ['off', 'on'][self.auto_update])
if ch in [ord('r'), ord('R')]:
self.markers[:] = 0
self.markers_vis[:] = self.img
self.sketch.show()
if ch in [ord('q'), ord('Q'), ord(' ')]:
# 清空标记和掩码
self.reset()
self.change_thresh()
self.preprocess(1)
self.watershed()
# 显示带有先验的图片
self.sketch.show()
cv.destroyAllWindows()
return self.vis
def write_matrix_to_file(self, matrix):
h, w = matrix.shape
name = "haha.txt"
f = open(name, "w")
for i in range(h):
for j in range(w):
f.write(str(int(matrix[i][j])))
f.write("\n")
f.close()
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()
if __name__ == '__main__':
import sys
try:
fn = sys.argv[1]
except:
fn = '../data/fruits.jpg'
print(__doc__)
img = cv2.imread(fn)
if img is None:
print('Failed to load image file:', fn)
sys.exit(1)
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 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()
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
class TestOCR:
ESC = 27
KEY_UP = 0
KEY_DOWN = 1
def __init__(self, model, filenames, flags, pattern):
self.ocr = OCR()
self.ocr.loadModel(model, OCR.MODEL_ANN, flags)
if filenames:
counter = {}
for filename in filenames:
ch = self.ocr.charFromFile(filename)
if pattern:
label = self.__exec(pattern, filename)
if label in counter:
predicted, total = counter[label]
counter[label] = (predicted + int(label == ch), total + 1)
else:
counter[label] = (int(label == ch), 1)
print "%s in %s" % (ch, filename)
if pattern:
self.__analyze(counter)
else:
h, w = 200, 200
img = np.zeros((h, w, 3), np.uint8)
img[:,:] = (255, 255, 255)
self.brush = Brush("Brush")
self.sketcher = Sketcher('Test OCR', img, self.brush)
def __analyze(self, counter):
print ""
totalPercent = []
for label, (predicted, total) in sorted(counter.iteritems()):
percent = int(float(predicted) / total * 100)
totalPercent.append(percent)
print "{0}\t{1} / {2} - {3} %".format(label, predicted, total, percent)
print "\nTotal recognized : {0:.1f} %\n".format(np.mean(totalPercent))
def __exec(self, file, arg):
out = subprocess.Popen([file, arg], stdout=subprocess.PIPE).communicate()[0]
return out
def __displayResponse(self, ch):
response = np.zeros((75, 75, 3), np.uint8)
response[:,:] = (255, 255, 255)
cv2.putText(response, ch, (15, 35), cv2.FONT_HERSHEY_PLAIN, 3.0, (0, 0, 0), 1)
cv2.imshow("Response", response)
def run(self):
while True:
k = cv2.waitKey(0) & 0xFF
if k == self.ESC:
break
elif k == ord('r'):
self.sketcher.reset()
self.sketcher.show()
elif k == ord(' '):
ch = self.ocr.charFromImage(self.sketcher.sketch)
self.sketcher.show()
self.sketcher.reset()
self.__displayResponse(ch)
print "OCR : %s" % ch
elif k == self.KEY_UP:
self.brush.brushSize += 1
elif k == self.KEY_DOWN:
self.brush.brushSize -= 1
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)
import numpy as np
import cv2
from common import Sketcher
img = cv2.imread('lc1.jpg')
mark = np.zeros(img.shape[:2], np.uint8)
sketch = Sketcher('img', [img, mark], lambda: ((255, 255, 255), 255))
dst = cv2.inpaint(img, mark, 3, cv2.INPAINT_TELEA)
cv2.imshow('dst', dst)
cv2.imshow('mark', mark)
cv2.imshow('sketch', sketch)
cv2.waitKey(0)
cv2.destroyAllWindows()
