def doneImages():
meta_json = os.path.join("stacked", "test_data.json")
with open(meta_json) as json_file:
data = json.load(json_file)
images = data["images"]
image_names = []
for image in images:
name = image["image_name"].split(".")[0]
image_names.append(name[:-7])
return image_names
#if __name__ == '__main__':
bombsCoor = [(39.0338362, -104.8850707), (39.0337238, -104.8842394)]
index = 0
imagePath = os.path.join('..', 'test_data')
for file in os.listdir(imagePath):
stripped_file = file.split(".")[0]
FILE = stripped_file[:-1]
if FILE not in doneImages():
print("stacking: " + FILE)
image_wild = FILE + '*.tif'
imageNames = glob.glob(os.path.join(imagePath, image_wild))
#panelNames = glob.glob(os.path.join(imagePath,'IMG_0111_*.tif'))
stack.stackImages(FILE, imageNames)
file = FILE + '3.tif'
data.createJson(file, bombsCoor)
index += 1
print(str(index) + " images stacked")
def driver():
'''
main driver code for the pulling 6 bands of an image, then stacking them, updating the metajson data
then push the stacked image and metadata back to the server
'''
#opening directpry json
filename = 'directory.json'
with open(filename) as json_file:
dir_json = json.load(json_file)
#getting down to each file on the server
sets = dir_json["files"]
for set in sets:
batches = dir_json["files"][set]
for batch in batches:
files = dir_json["files"][set][batch]
for file in files:
#baseName is the file name without its band number
baseName = file.split('_')[0] + '_' + file.split('_')[1] + '_'
# checking if the file has already been stacked
if check_uploads(baseName):
#post current working file
post_current_file(baseName)
#getting each band for the image
for band in range(1, 7):
image = baseName + str(band) + '.tif'
url = baseURL + '/' + "files" + '/' + set + '/' + batch + '/' + image
print(url)
#pullling the image band
pull_image(url)
#giving the images to stack function
image_wild = baseName + '*.tif'
imagePath = os.path.join('..', 'data')
imageNames = glob.glob(os.path.join(imagePath, image_wild))
successCode = stack.stackImages(baseName, imageNames)
if successCode != -1:
file = baseName + '3.tif'
data.updateDatabase(file, bombsCoor)
stacked = '../processing/stacked/' + baseName + 'stacked.tiff'
os.remove(stacked)
else:
#error handling
print(baseName + ' skipped due to stacking errors')
#adding file to errorFile.txt
update_errorFiles(baseName)
#deleting the bands
delete_images(image_wild)
##takes a really long time to run
sr = dnn_superres.DnnSuperResImpl_create()
image = cv2.imread('Ressources/picture_png_1.PNG')
image2 = cv2.imread('Ressources/picture_png_2.PNG')
image3 = cv2.imread('Ressources/picture_png_3.PNG')
image5 = cv2.imread('Ressources/picture_png_5.PNG')
path = "Ressources/EDSR_x4_best_performing.pb"
sr.readModel(path)
sr.setModel("edsr", 4)
result = sr.upsample(image)
result2 = sr.upsample(image2)
result3 = sr.upsample(image3)
result5 = sr.upsample(image5)
cv2.imwrite("./upscaled1.png", result)
cv2.imwrite("./upscaled2.png", result2)
cv2.imwrite("./upscaled3.png", result3)
cv2.imwrite("./upscaled5.png", result5)
imgStack = stackImages(
0.5,
([image, result], [image2, result2], [image3, result3], [image5, result5]))
cv2.imshow("stacked", imgStack)
cv2.waitKey(0)
cv.resizeWindow("TrackBars", width, height)
cv.createTrackbar("Hue Min", "TrackBars", 29, 179, empty)
cv.createTrackbar("Hue Max", "TrackBars", 179, 179, empty)
cv.createTrackbar("Sat Min", "TrackBars", 39, 255, empty)
cv.createTrackbar("Sat Max", "TrackBars", 255, 255, empty)
cv.createTrackbar("Val Min", "TrackBars", 43, 255, empty)
cv.createTrackbar("Val Max", "TrackBars", 255, 255, empty)
while (cv.waitKey(1) != ord('q')):
success, img = cam.read()
imgHSV = cv.cvtColor(img, cv.COLOR_BGR2HSV)
h_min = cv.getTrackbarPos("Hue Min", "TrackBars")
h_max = cv.getTrackbarPos("Hue Max", "TrackBars")
s_min = cv.getTrackbarPos("Sat Min", "TrackBars")
s_max = cv.getTrackbarPos("Sat Max", "TrackBars")
v_min = cv.getTrackbarPos("Val Min", "TrackBars")
v_max = cv.getTrackbarPos("Val Max", "TrackBars")
lower = np.array([h_min, s_min, v_min])
upper = np.array([h_max, s_max, v_max])
mask = cv.inRange(imgHSV, lower, upper)
imgRes = cv.bitwise_and(img, img, mask=mask)
imgStack = stackImages(1, ([img, imgHSV, imgRes]))
cv.imshow("Video", imgStack)
else:
objectType = "Rectangle"
elif (objCor > 4):
objectType = "Circle"
else:
objectType = "None"
cv.rectangle(imgContour, (x, y), (w + x, h + y), (0, 0xff, 0), 2)
cv.putText(imgContour, objectType,
(x + (w // 2) - 10, y + (h // 2) - 10),
cv.FONT_HERSHEY_COMPLEX, 0.5, (0, 0, 0), 2)
path = "/home/london/Pictures/OpenCV/shapes.png"
img = cv.imread(path)
imgContour = img.copy()
imgGray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
imgBlur = cv.GaussianBlur(imgGray, (7, 7), 1)
imgCanny = cv.Canny(imgBlur, 50, 50)
getContours(imgCanny)
imgBlank = np.zeros_like(img)
imgStack = stackImages(
0.8, ([img, imgGray, imgBlur], [imgCanny, imgContour, imgBlank]))
cv.imshow("Stacked images", imgStack)
#cv.imshow("Original", img)
#cv.imshow("Grayed Image", imgGray)
#cv.imshow("Blurred Image", imgBlur)
while (cv.waitKey(1) != ord('q')):
pass
def start_track_bar(self):
cv2.namedWindow("TrackBars")
cv2.resizeWindow("TrackBars", 640, 240)
cv2.createTrackbar("Hue Min", "TrackBars", 0, 179,
self.on_track_bar_change)
cv2.createTrackbar("Hue Max", "TrackBars", 179, 179,
self.on_track_bar_change)
cv2.createTrackbar("Sat Min", "TrackBars", 0, 255,
self.on_track_bar_change)
cv2.createTrackbar("Sat Max", "TrackBars", 255, 255,
self.on_track_bar_change)
cv2.createTrackbar("Val Min", "TrackBars", 0, 255,
self.on_track_bar_change)
cv2.createTrackbar("Val Max", "TrackBars", 255, 255,
self.on_track_bar_change)
image_camera_monde = cv2.imread("trajectory_example_3.jpg")
GLARE_MIN = np.array([0, 0, 20], np.uint8)
GLARE_MAX = np.array([0, 0, 255], np.uint8)
hsv_img = cv2.cvtColor(image_camera_monde, cv2.COLOR_BGR2HSV)
frame_threshed = cv2.inRange(hsv_img, GLARE_MIN, GLARE_MAX)
result = cv2.inpaint(image_camera_monde, frame_threshed, 0.6,
cv2.INPAINT_TELEA)
lab1 = cv2.cvtColor(result, cv2.COLOR_BGR2LAB)
lab_planes1 = cv2.split(lab1)
clahe1 = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
lab_planes1[0] = clahe1.apply(lab_planes1[0])
lab1 = cv2.merge(lab_planes1)
image = cv2.cvtColor(lab1, cv2.COLOR_LAB2BGR)
imghsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV).astype("float32")
(h, s, v) = cv2.split(imghsv)
s = s * 2
s = np.clip(s, 0, 255)
imghsv = cv2.merge([h, s, v])
image = cv2.cvtColor(imghsv.astype("uint8"), cv2.COLOR_HSV2BGR)
hsvImg = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
hsvImg[..., 2] = hsvImg[..., 2] * 0.8
image_camera_monde = cv2.cvtColor(hsvImg, cv2.COLOR_HSV2BGR)
while True:
hsv_image = cv2.cvtColor(image_camera_monde, cv2.COLOR_BGR2HSV)
h_min = cv2.getTrackbarPos("Hue Min", "TrackBars")
h_max = cv2.getTrackbarPos("Hue Max", "TrackBars")
s_min = cv2.getTrackbarPos("Sat Min", "TrackBars")
s_max = cv2.getTrackbarPos("Sat Max", "TrackBars")
v_min = cv2.getTrackbarPos("Val Min", "TrackBars")
v_max = cv2.getTrackbarPos("Val Max", "TrackBars")
print(h_min, s_min, v_min, h_max, s_max, v_max)
lower = np.array([h_min, s_min, v_min])
upper = np.array([h_max, s_max, v_max])
mask = cv2.inRange(hsv_image, lower, upper)
image_result = cv2.bitwise_and(image_camera_monde,
image_camera_monde,
mask=mask)
image_stack = stack_images.stackImages(
0.6, ([image_camera_monde, hsv_image], [mask, image_result]))
cv2.imshow("Image hsv", image_stack)
cv2.waitKey(2000)
#Joining images
import cv2 as cv
import numpy as np
from stack_images import stackImages
img = cv.imread("/home/london/Pictures/OpenCV/train/cat.1.jpg")
img2 = cv.imread("/home/london/Pictures/OpenCV/train/cat.2.jpg")
imgGray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
hor = np.hstack((img, img))
ver = np.vstack((img, img, img))
scaled = stackImages(0.5, ([img, img2]))
print(img.shape)
print(hor.shape)
print(ver.shape)
cv.imshow("Vertical", ver)
cv.imshow("Horizontal", hor)
cv.imshow("Original", img)
cv.imshow("Scaled", scaled)
while (not ((cv.waitKey(1) == ord('q')))):
pass
cv.createTrackbar("Sat Max", "TrackBars", 255, 255, empty)
cv.createTrackbar("Val Min", "TrackBars", 114, 255, empty)
cv.createTrackbar("Val Max", "TrackBars", 255, 255, empty)
imgHSV = cv.cvtColor(img, cv.COLOR_BGR2HSV)
while (cv.waitKey(1) != ord('q')):
h_min = cv.getTrackbarPos("Hue Min", "TrackBars")
h_max = cv.getTrackbarPos("Hue Max", "TrackBars")
s_min = cv.getTrackbarPos("Sat Min", "TrackBars")
s_max = cv.getTrackbarPos("Sat Max", "TrackBars")
v_min = cv.getTrackbarPos("Val Min", "TrackBars")
v_max = cv.getTrackbarPos("Val Max", "TrackBars")
lower = np.array([h_min, s_min, v_min])
upper = np.array([h_max, s_max, v_max])
mask = cv.inRange(imgHSV, lower, upper)
imgRes = cv.bitwise_and(img, img, mask=mask)
cv.imshow("Original", img)
#cv.imshow("HSV", imgHSV)
#cv.imshow("Mask", mask)
#cv.imshow("Result", imgRes)
imgStack = stackImages(0.6, ([img, imgHSV], [mask, imgRes]))
cv.imshow("Stacked images", imgStack)