本文整理汇总了Python中cv2.imwrite方法的典型用法代码示例。如果您正苦于以下问题:Python cv2.imwrite方法的具体用法?Python cv2.imwrite怎么用?Python cv2.imwrite使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在模块cv2的用法示例。
在下文中一共展示了cv2.imwrite方法的28个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的Python代码示例。
示例1: main
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def main():
imagePath = "img.jpg"
img = cv2.imread(imagePath)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
generate_histogram(gray)
cv2.imwrite("before.jpg", gray)
gray = cv2.equalizeHist(gray)
generate_histogram(gray)
cv2.imwrite("after.jpg",gray)
return 0
开发者ID:felipecorrea,项目名称:pedestrian-haar-based-detector,代码行数:19,
示例2: saveimageWithMask
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def saveimageWithMask(img, outname, mask_poly):
dstimg = copy.deepcopy(img)
for mask in mask_poly:
bound = mask.bounds
if (len(bound) < 4):
continue
xmin, ymin, xmax, ymax = bound[0], bound[1], bound[2], bound[3]
for x in range(int(xmin), int(xmax)):
for y in range(int(ymin), int(ymax)):
point = shgeo.Point(x, y)
if point.within(mask):
#print('withing')
dstimg[int(y)][int(x)] = 0
cv2.imwrite(outname, dstimg)
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:19,
示例3: _lapulaseDetection
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def _lapulaseDetection(self, imgName):
"""
:param strdir: 文件所在的目录
:param name: 文件名称
:return: 检测模糊后的分数
"""
# step1: 预处理
img2gray, reImg = self.preImgOps(imgName)
# step2: laplacian算子 获取评分
resLap = cv2.Laplacian(img2gray, cv2.CV_64F)
score = resLap.var()
print("Laplacian %s score of given image is %s", str(score))
# strp3: 绘制图片并保存 不应该写在这里 抽象出来 这是共有的部分
newImg = self._drawImgFonts(reImg, str(score))
newDir = self.strDir + "/_lapulaseDetection_/"
if not os.path.exists(newDir):
os.makedirs(newDir)
newPath = newDir + imgName
# 显示
cv2.imwrite(newPath, newImg) # 保存图片
cv2.imshow(imgName, newImg)
cv2.waitKey(0)
# step3: 返回分数
return score
开发者ID:Leezhen2014,项目名称:python--,代码行数:27,
示例4: visual
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def visual(title, X, activation):
'''create a grid of images and save it as a final image
title : grid image name
X : array of images
'''
assert len(X.shape) == 4
X = X.transpose((0, 2, 3, 1))
if activation == 'sigmoid':
X = np.clip((X)*(255.0), 0, 255).astype(np.uint8)
elif activation == 'tanh':
X = np.clip((X+1.0)*(255.0/2.0), 0, 255).astype(np.uint8)
n = np.ceil(np.sqrt(X.shape[0]))
buff = np.zeros((int(n*X.shape[1]), int(n*X.shape[2]), int(X.shape[3])), dtype=np.uint8)
for i, img in enumerate(X):
fill_buf(buff, i, img, X.shape[1:3])
cv2.imwrite('%s.jpg' % (title), buff)
开发者ID:awslabs,项目名称:dynamic-training-with-apache-mxnet-on-aws,代码行数:19,
示例5: convert_images2bmp
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def convert_images2bmp():
# cv2.imread() jpg at 230 img/s, *.bmp at 400 img/s
for path in ['../coco/images/val2014/', '../coco/images/train2014/']:
folder = os.sep + Path(path).name
output = path.replace(folder, folder + 'bmp')
if os.path.exists(output):
shutil.rmtree(output) # delete output folder
os.makedirs(output) # make new output folder
for f in tqdm(glob.glob('%s*.jpg' % path)):
save_name = f.replace('.jpg', '.bmp').replace(folder, folder + 'bmp')
cv2.imwrite(save_name, cv2.imread(f))
for label_path in ['../coco/trainvalno5k.txt', '../coco/5k.txt']:
with open(label_path, 'r') as file:
lines = file.read()
lines = lines.replace('2014/', '2014bmp/').replace('.jpg', '.bmp').replace(
'/Users/glennjocher/PycharmProjects/', '../')
with open(label_path.replace('5k', '5k_bmp'), 'w') as file:
file.write(lines)
开发者ID:zbyuan,项目名称:pruning_yolov3,代码行数:22,
示例6: crop_images_random
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def crop_images_random(path='../images/', scale=0.50): # from utils.utils import *; crop_images_random()
# crops images into random squares up to scale fraction
# WARNING: overwrites images!
for file in tqdm(sorted(glob.glob('%s/*.*' % path))):
img = cv2.imread(file) # BGR
if img is not None:
h, w = img.shape[:2]
# create random mask
a = 30 # minimum size (pixels)
mask_h = random.randint(a, int(max(a, h * scale))) # mask height
mask_w = mask_h # mask width
# box
xmin = max(0, random.randint(0, w) - mask_w // 2)
ymin = max(0, random.randint(0, h) - mask_h // 2)
xmax = min(w, xmin + mask_w)
ymax = min(h, ymin + mask_h)
# apply random color mask
cv2.imwrite(file, img[ymin:ymax, xmin:xmax])
开发者ID:zbyuan,项目名称:pruning_yolov3,代码行数:23,
示例7: test
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def test(test_loader, model, logger=None, Writer=None):
model.eval()
with torch.no_grad():
for its, (img_line, img_noise) in enumerate(test_loader):
img_line = img_line.cuda() if torch.cuda.is_available() else img_line
img_noise = img_noise.cuda() if torch.cuda.is_available() else img_noise
g_results = model(torch.cat((img_line, img_noise), 1))
for i in range(img_line.shape[0]):
img_line_test = img_line[i].cpu().numpy().transpose((1,2,0)) * 255
img_line_test = img_line_test.squeeze()
cv2.imwrite((cfg.PATH.RES_TEST+"line_{}.jpg".format(i+its)), img_line_test)
img_res_test = g_results[i].cpu().numpy().transpose((1,2,0)) * 255
cv2.imwrite((cfg.PATH.RES_TEST+"res_{}.jpg".format(i+its)), img_res_test)
print("{}/{}".format(i+its,its_num))
开发者ID:HaiyangLiu1997,项目名称:Pytorch-Networks,代码行数:18,
示例8: on_epoch_end
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def on_epoch_end(self, epoch, logs=None):
if self.tiny:
anchors = yolo_tiny_anchors
masks = yolo_tiny_anchor_masks
else:
anchors = yolo_anchors
masks = yolo_anchor_masks
model = make_eval_model_from_trained_model(self.model, anchors, masks)
epoch_dir = os.path.join(self.result_dir, str(epoch))
os.makedirs(epoch_dir)
for batch, (images, labels) in enumerate(self.dataset):
images = images.numpy()
for i in range(images.shape[0]):
boxes, scores, classes = model.predict(images[i:i + 1, ...])
img_for_this = (images[i, ...] * 255).astype(np.uint8)
boxes_for_this, scores_for_this, classes_for_this = boxes[0, ...], scores[0, ...], classes[0, ...]
img_for_this = draw_outputs(img_for_this, (boxes_for_this, scores_for_this, classes_for_this))
cv2.imwrite(os.path.join(epoch_dir, '{0}.jpg'.format(uuid.uuid4())), img_for_this)
if batch == self.num_batches:
break
开发者ID:akkaze,项目名称:tf2-yolo3,代码行数:26,
示例9: _blurDetection
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def _blurDetection(self, imgName):
# step 1 图像的预处理
img2gray, reImg = self.preImgOps(imgName)
imgMat=self._imageToMatrix(img2gray)/255.0
x, y = imgMat.shape
score = 0
for i in range(x - 2):
for j in range(y - 2):
score += (imgMat[i + 2, j] - imgMat[i, j]) ** 2
# step3: 绘制图片并保存 不应该写在这里 抽象出来 这是共有的部分
score=score/10
newImg = self._drawImgFonts(reImg, str(score))
newDir = self.strDir + "/_blurDetection_/"
if not os.path.exists(newDir):
os.makedirs(newDir)
newPath = newDir + imgName
cv2.imwrite(newPath, newImg) # 保存图片
cv2.imshow(imgName, newImg)
cv2.waitKey(0)
return score
开发者ID:Leezhen2014,项目名称:python--,代码行数:23,
示例10: _SMDDetection
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def _SMDDetection(self, imgName):
# step 1 图像的预处理
img2gray, reImg = self.preImgOps(imgName)
f=self._imageToMatrix(img2gray)/255.0
x, y = f.shape
score = 0
for i in range(x - 1):
for j in range(y - 1):
score += np.abs(f[i+1,j]-f[i,j])+np.abs(f[i,j]-f[i+1,j])
# strp3: 绘制图片并保存 不应该写在这里 抽象出来 这是共有的部分
score=score/100
newImg = self._drawImgFonts(reImg, str(score))
newDir = self.strDir + "/_SMDDetection_/"
if not os.path.exists(newDir):
os.makedirs(newDir)
newPath = newDir + imgName
cv2.imwrite(newPath, newImg) # 保存图片
cv2.imshow(imgName, newImg)
cv2.waitKey(0)
return score
开发者ID:Leezhen2014,项目名称:python--,代码行数:23,
示例11: _SMD2Detection
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def _SMD2Detection(self, imgName):
"""
灰度方差乘积
:param imgName:
:return:
"""
# step 1 图像的预处理
img2gray, reImg = self.preImgOps(imgName)
f=self._imageToMatrix(img2gray)/255.0
x, y = f.shape
score = 0
for i in range(x - 1):
for j in range(y - 1):
score += np.abs(f[i+1,j]-f[i,j])*np.abs(f[i,j]-f[i,j+1])
# strp3: 绘制图片并保存 不应该写在这里 抽象出来 这是共有的部分
score=score
newImg = self._drawImgFonts(reImg, str(score))
newDir = self.strDir + "/_SMD2Detection_/"
if not os.path.exists(newDir):
os.makedirs(newDir)
newPath = newDir + imgName
cv2.imwrite(newPath, newImg) # 保存图片
cv2.imshow(imgName, newImg)
cv2.waitKey(0)
return score
开发者ID:Leezhen2014,项目名称:python--,代码行数:27,
示例12: _Variance
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def _Variance(self, imgName):
"""
灰度方差乘积
:param imgName:
:return:
"""
# step 1 图像的预处理
img2gray, reImg = self.preImgOps(imgName)
f = self._imageToMatrix(img2gray)
# strp3: 绘制图片并保存 不应该写在这里 抽象出来 这是共有的部分
score = np.var(f)
newImg = self._drawImgFonts(reImg, str(score))
newDir = self.strDir + "/_Variance_/"
if not os.path.exists(newDir):
os.makedirs(newDir)
newPath = newDir + imgName
cv2.imwrite(newPath, newImg) # 保存图片
cv2.imshow(imgName, newImg)
cv2.waitKey(0)
return score
开发者ID:Leezhen2014,项目名称:python--,代码行数:23,
示例13: make_edge_smooth
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def make_edge_smooth(dataset_name, img_size) :
check_folder('./dataset/{}/{}'.format(dataset_name, 'trainB_smooth'))
file_list = glob('./dataset/{}/{}/*.*'.format(dataset_name, 'trainB'))
save_dir = './dataset/{}/trainB_smooth'.format(dataset_name)
kernel_size = 5
kernel = np.ones((kernel_size, kernel_size), np.uint8)
gauss = cv2.getGaussianKernel(kernel_size, 0)
gauss = gauss * gauss.transpose(1, 0)
for f in tqdm(file_list) :
file_name = os.path.basename(f)
bgr_img = cv2.imread(f)
gray_img = cv2.imread(f, 0)
bgr_img = cv2.resize(bgr_img, (img_size, img_size))
pad_img = np.pad(bgr_img, ((2, 2), (2, 2), (0, 0)), mode='reflect')
gray_img = cv2.resize(gray_img, (img_size, img_size))
edges = cv2.Canny(gray_img, 100, 200)
dilation = cv2.dilate(edges, kernel)
gauss_img = np.copy(bgr_img)
idx = np.where(dilation != 0)
for i in range(np.sum(dilation != 0)):
gauss_img[idx[0][i], idx[1][i], 0] = np.sum(
np.multiply(pad_img[idx[0][i]:idx[0][i] + kernel_size, idx[1][i]:idx[1][i] + kernel_size, 0], gauss))
gauss_img[idx[0][i], idx[1][i], 1] = np.sum(
np.multiply(pad_img[idx[0][i]:idx[0][i] + kernel_size, idx[1][i]:idx[1][i] + kernel_size, 1], gauss))
gauss_img[idx[0][i], idx[1][i], 2] = np.sum(
np.multiply(pad_img[idx[0][i]:idx[0][i] + kernel_size, idx[1][i]:idx[1][i] + kernel_size, 2], gauss))
cv2.imwrite(os.path.join(save_dir, file_name), gauss_img)
开发者ID:taki0112,项目名称:CartoonGAN-Tensorflow,代码行数:37,
示例14: loop2
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def loop2(self,text,w=1280,h=720):
cap = cv2.VideoCapture(int(text))
cap.set(6 ,cv2.VideoWriter_fourcc('M', 'J', 'P', 'G') );
global capnum2
capnum2 = int(text)
cap.set(3,w);
cap.set(4,h);
global update2
update2 = 1
global shotmark2
while (update2 == 1):
ret, frame = cap.read()
if shotmark2 == 1:
fn = self.lineEdit.text()
name = "photo/2_"+fn + "video.jpg"
if os.path.exists(name):
name = "photo/2_" + fn + "video"+str(int(time.time()))+".jpg"
cv2.imwrite(name, frame)
shotmark2 = 0
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
self.original2_image.updateImage(frame)
# cap.release()
cv_img_rgb = np.zeros((700,700,3))
self.original2_image.updateImage(cv_img_rgb)
开发者ID:anonymouslycn,项目名称:bjtu_BinocularCameraRecord,代码行数:27,
示例15: degrade_images_in_folder
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def degrade_images_in_folder(
folder,
dst_folder_suffix,
LIGHTDOWN=True,
UNBALANCECOLOR=True,):
import os
js = os.listdir(folder)
dst_folder = folder + '-' + dst_folder_suffix
try:
os.mkdir(dst_folder)
except:
print('dir exist!')
print('in ' + dst_folder)
num = 3
for j in js:
img = cv2.imread(folder + '/' + j) / 255.
if LIGHTDOWN:
for _ in range(num - 1):
out = pow(img, np.random.uniform(0.4, 0.6)) * np.random.uniform(
0.25, 0.5)
cv2.imwrite(dst_folder + '/' + ('L%d-' % _) + j, out * 255.)
out = img * img
out = out * (1.0 / out.max())
cv2.imwrite(dst_folder + '/' + ('L%d-' % num) + j, out * 255.)
if UNBALANCECOLOR:
filter = WB2()
outs = np.array([img] * num)
features = np.abs(np.random.rand(num, 3))
for _, out in enumerate(
filter.process(outs, filter.filter_param_regressor(features))):
# print out.max()
out /= out.max()
out *= np.random.uniform(0.7, 1)
cv2.imwrite(dst_folder + '/' + ('C%d-' % _) + j, out * 255.)
开发者ID:yuanming-hu,项目名称:exposure,代码行数:36,
示例16: vis_images_and_indexs
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def vis_images_and_indexs(images, features, dir, name):
# indexs = np.reshape(indexs, (len(indexs),))
# print('visualizing images and indexs: ', images.shape, indexs.shape)
id_imgs = []
for feature in features:
img = np.ones((64, 64, 3))
cv2.putText(img,
str(feature), (4, 33), cv2.FONT_HERSHEY_SIMPLEX, 0.25,
(1.0, 0.0, 0.0))
id_imgs.append(img)
id_imgs = np.stack(id_imgs, axis=0)
# print('id imgs: ', id_imgs.shape)
vis_imgs = np.vstack([images, id_imgs])
image = make_image_grid(vis_imgs, per_row=images.shape[0])
vis_dir = dir
try:
os.mkdir(vis_dir)
except:
pass
cv2.imwrite(os.path.join(vis_dir, name + '.png'), image[:, :, ::-1] * 255.0)
开发者ID:yuanming-hu,项目名称:exposure,代码行数:23,
示例17: test_motion
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def test_motion():
image = cv2.imread("./imgs/image.jpeg")
print(image.shape)
detector = Detector_Motion()
image2 = cv2.imread("./imgs/image_box.jpg")
print(image2.shape)
assert image.shape == image2.shape
image2 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)
image2 = cv2.GaussianBlur(image2, (21, 21), 0)
detector.avg = image2.astype(float)
output = detector.prediction(image)
df = detector.filter_prediction(output, image)
image = detector.draw_boxes(image, df)
print(df)
assert df.shape[0] == 1
cv2.imwrite("./imgs/outputcv.jpg", image)
开发者ID:cristianpb,项目名称:object-detection,代码行数:22,
示例18: CaptureContinous
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def CaptureContinous(self, detector):
cap = cv2.VideoCapture(0)
_, image = cap.read()
cap.release()
output = detector.prediction(image)
df = detector.filter_prediction(output, image)
if len(df) > 0:
if (df['class_name']
.str
.contains('person|bird|cat|wine glass|cup|sandwich')
.any()):
day = datetime.now().strftime("%Y%m%d")
directory = os.path.join(IMAGE_FOLDER, 'webcam', day)
if not os.path.exists(directory):
os.makedirs(directory)
image = detector.draw_boxes(image, df)
classes = df['class_name'].unique().tolist()
hour = datetime.now().strftime("%H%M%S")
filename_output = os.path.join(
directory, "{}_{}_.jpg".format(hour, "-".join(classes))
)
cv2.imwrite(filename_output, image)
开发者ID:cristianpb,项目名称:object-detection,代码行数:24,
示例19: extract_faces
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def extract_faces(emotions):
"""
Crops faces in emotions images.
:param emotions: List of emotions names.
"""
print("Extracting faces")
for emotion in emotions:
photos = glob.glob('data/sorted_set/%s/*' % emotion)
for file_number, photo in enumerate(photos):
frame = cv2.imread(photo)
normalized_faces = find_faces(frame)
os.remove(photo)
for face in normalized_faces:
try:
cv2.imwrite("data/sorted_set/%s/%s.png" % (emotion, file_number + 1), face[0]) # write image
except:
print("error in processing %s" % photo)
开发者ID:PiotrDabrowskey,项目名称:facemoji,代码行数:21,
示例20: func1
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def func1(k=None):
if not k:
k=randint(0, 20)
print('image is',k)
for i, (img, heatmap,vecmap,depthmap,kpt_3d) in enumerate(train_loader):
if i==k:
# test_heatmaps(heatmap,img,i)
# test_vecmaps(vecmap,img,i)
# edges = [[0, 1], [1, 2], [2, 6], [6, 3], [3, 4], [4, 5], [10, 11], [11, 12], [12, 8], [8, 13], [13, 14], [14, 15], [6, 8], [8, 9]]
# ppl=kpt_3d.shape[0]
# for i in range(ppl):
# for edge in edges:
# cv2.line(img,(int(kpt_3d[i][edge[0]][0]),int(kpt_3d[i][edge[0]][1])),(int(kpt_3d[i][edge[1]][0]),int(kpt_3d[i][edge[1]][1])),(0,255,0))
# cv2.imwrite('outside3dfinal.png',img)
return img,heatmap,vecmap,depthmap,kpt_3d
开发者ID:Naman-ntc,项目名称:3D-HourGlass-Network,代码行数:18,代码来源:my.py
示例21: undistort_images
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def undistort_images(src, dst):
"""
undistort the images in src folder to dst folder
"""
# load dst, mtx
pickle_file = open("../camera_cal/camera_cal.p", "rb")
dist_pickle = pickle.load(pickle_file)
mtx = dist_pickle["mtx"]
dist = dist_pickle["dist"]
pickle_file.close()
# loop the image folder
image_files = glob.glob(src+"*.jpg")
for idx, file in enumerate(image_files):
print(file)
img = mpimg.imread(file)
image_dist = cv2.undistort(img, mtx, dist, None, mtx)
file_name = file.split("\\")[-1]
print(file_name)
out_image = dst+file_name
print(out_image)
image_dist = cv2.cvtColor(image_dist, cv2.COLOR_RGB2BGR)
cv2.imwrite(out_image, image_dist)
开发者ID:ChengZhongShen,项目名称:Advanced_Lane_Lines,代码行数:25,
示例22: wrap_images
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def wrap_images(src, dst):
"""
apply the wrap to images
"""
# load M, Minv
img_size = (1280, 720)
pickle_file = open("../helper/trans_pickle.p", "rb")
trans_pickle = pickle.load(pickle_file)
M = trans_pickle["M"]
Minv = trans_pickle["Minv"]
# loop the file folder
image_files = glob.glob(src+"*.jpg")
for idx, file in enumerate(image_files):
print(file)
img = mpimg.imread(file)
image_wraped = cv2.warpPerspective(img, M, img_size, flags=cv2.INTER_LINEAR)
file_name = file.split("\\")[-1]
print(file_name)
out_image = dst+file_name
print(out_image)
# no need to covert RGB to BGR since 3 channel is same
image_wraped = cv2.cvtColor(image_wraped, cv2.COLOR_RGB2BGR)
cv2.imwrite(out_image, image_wraped)
开发者ID:ChengZhongShen,项目名称:Advanced_Lane_Lines,代码行数:25,
示例23: test_thresh_images
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def test_thresh_images(src, dst, s_thresh, sx_thresh):
"""
apply the thresh to images in a src folder and output to dst foler
"""
image_files = glob.glob(src+"*.jpg")
for idx, file in enumerate(image_files):
print(file)
img = mpimg.imread(file)
image_threshed = color_grid_thresh(img, s_thresh=s_thresh, sx_thresh=sx_thresh)
file_name = file.split("\\")[-1]
print(file_name)
out_image = dst+file_name
print(out_image)
# convert binary to RGB, *255, to visiual, 1 will not visual after write to file
image_threshed = cv2.cvtColor(image_threshed*255, cv2.COLOR_GRAY2RGB)
cv2.imwrite(out_image, image_threshed)
开发者ID:ChengZhongShen,项目名称:Advanced_Lane_Lines,代码行数:18,
示例24: test_yellow_grid_thresh_images
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def test_yellow_grid_thresh_images(src, dst, y_low=(10,50,0), y_high=(30,255,255), sx_thresh=(20, 100)):
"""
apply the thresh to images in a src folder and output to dst foler
"""
image_files = glob.glob(src+"*.jpg")
for idx, file in enumerate(image_files):
print(file)
img = mpimg.imread(file)
image_threshed = yellow_grid_thresh(img, y_low, y_high, sx_thresh)
file_name = file.split("\\")[-1]
print(file_name)
out_image = dst+file_name
print(out_image)
# convert binary to RGB, *255, to visiual, 1 will not visual after write to file
image_threshed = cv2.cvtColor(image_threshed*255, cv2.COLOR_GRAY2RGB)
cv2.imwrite(out_image, image_threshed)
开发者ID:ChengZhongShen,项目名称:Advanced_Lane_Lines,代码行数:19,
示例25: test_yellow_white_thresh_images
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def test_yellow_white_thresh_images(src, dst, y_low=(10,50,0), y_high=(30,255,255), w_low=(180,180,180), w_high=(255,255,255)):
"""
apply the thresh to images in a src folder and output to dst foler
"""
image_files = glob.glob(src+"*.jpg")
for idx, file in enumerate(image_files):
print(file)
img = mpimg.imread(file)
image_threshed = yellow_white_thresh(img, y_low, y_high, w_low, w_high)
file_name = file.split("\\")[-1]
print(file_name)
out_image = dst+file_name
print(out_image)
# convert binary to RGB, *255, to visiual, 1 will not visual after write to file
image_threshed = cv2.cvtColor(image_threshed*255, cv2.COLOR_GRAY2RGB)
# HSV = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
# V = HSV[:,:,2]
# brightness = np.mean(V)
# info_str = "brightness is: {}".format(int(brightness))
# cv2.putText(image_threshed, info_str, (50,700), cv2.FONT_HERSHEY_SIMPLEX,2,(0,255,255),2)
cv2.imwrite(out_image, image_threshed)
开发者ID:ChengZhongShen,项目名称:Advanced_Lane_Lines,代码行数:26,
示例26: main
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def main():
#IMG PATHS
imagePath = "test3.jpg"
cascPath = "cascades/haarcascade_pedestrian.xml"
pplCascade = cv2.CascadeClassifier(cascPath)
image = cv2.imread(imagePath)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = normalize_grayimage(gray)
pedestrians = pplCascade.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=10,
minSize=(32,96),
flags = cv2.cv.CV_HAAR_SCALE_IMAGE
)
print "Found {0} ppl!".format(len(pedestrians))
#Draw a rectangle around the detected objects
for (x, y, w, h) in pedestrians:
cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
cv2.imwrite("saida.jpg", image)
cv2.imshow("Ppl found", image)
cv2.waitKey(0)
return 0
开发者ID:felipecorrea,项目名称:pedestrian-haar-based-detector,代码行数:32,
示例27: main
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def main():
parser = argparse.ArgumentParser()
parser.add_argument("font_path", help="Path to ttf font file")
parser.add_argument("output", help="Output filename including extension (e.g. 'sample.jpg')")
parser.add_argument("--num", help="Up to 4 digit number [Default: random]")
args = parser.parse_args()
captcha = ImageCaptcha(fonts=[args.font_path])
captcha_str = args.num if args.num else DigitCaptcha.get_rand(3, 4)
img = captcha.generate(captcha_str)
img = np.fromstring(img.getvalue(), dtype='uint8')
img = cv2.imdecode(img, cv2.IMREAD_GRAYSCALE)
cv2.imwrite(args.output, img)
print("Captcha image with digits {} written to {}".format([int(c) for c in captcha_str], args.output))
开发者ID:awslabs,项目名称:dynamic-training-with-apache-mxnet-on-aws,代码行数:16,
示例28: ImgFormT
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# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import imwrite [as 别名]
def ImgFormT(srcpath, dstpath, srcform, dstform):
namelist = GetFileFromThisRootDir(srcpath, srcform)
for imgname in namelist:
src = cv2.imread(imgname)
basename = os.path.splitext(os.path.basename(imgname))[0]
cv2.imwrite(os.path.join(dstpath, basename + dstform), src)
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:8,
注:本文中的cv2.imwrite方法示例整理自Github/MSDocs等源码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。