Sample Image
Hello,
I created an application in python that select the Region of Interest(ROI) of an image, record and label it. But I has a limit of one ROI per image, anyone know how to have multiple selection of ROI per image? Also on attached image, as you can see I have multiple window, I want it to be in one window with different options, what packages are use on this kind of application.
here's my code in python using opencv2. Thank you in advance for the help
for image in filelist:
img = cv2.imread(image)
fromCenter = False
r = cv2.selectROI(img, fromCenter)
lbl = simpledialog.askstring("Image Label", "Please Enter Label")
result = eTree.SubElement(results, "Image")
path = eTree.SubElement(result, 'Path')
roi = eTree.SubElement(result, 'ROI')
label = eTree.SubElement(result, 'Label')
path.text = str(image)
roi.text = str(r)
label.text = str(lbl)
tree = eTree.ElementTree(results)
i = i + 1
if i == count:
format = [('XML Files', '*.xml'), ('All Files', '*.*')]
save = filedialog.asksaveasfilename(filetype=format, defaultextension='*.xml')
tree.write(save, xml_declaration=True, encoding='utf-8', method="xml")
Well at least for the first part of the question, have you considered to try the cv2.createROIs() instead of cv2.createROI() ? When the image window is opened you then select your first ROI and press enter, then the second and press enter etc. And when you are finished then press the escape key. It returns x,y,w,h of each ROI. Note that you will have to change your code accordingly but it will allow you to select multiple ROI.
Input image:
Example:
import cv2
img = cv2.imread('rois.png')
fromCenter = False
ROIs = cv2.selectROIs('Select ROIs', img, fromCenter)
ROI_1 = img[ROIs[0][1]:ROIs[0][1]+ROIs[0][3], ROIs[0][0]:ROIs[0][0]+ROIs[0][2]]
ROI_2 = img[ROIs[1][1]:ROIs[1][1]+ROIs[1][3], ROIs[1][0]:ROIs[1][0]+ROIs[1][2]]
ROI_3 = img[ROIs[2][1]:ROIs[2][1]+ROIs[2][3], ROIs[2][0]:ROIs[2][0]+ROIs[2][2]]
cv2.imshow('1', ROI_1)
cv2.imshow('2', ROI_2)
cv2.imshow('3', ROI_3)
cv2.waitKey(0)
cv2.destroyAllWindows()
Result:
For custom ROI you can use EasyROI. It supports rectangle, line, circle and polygon.
For using it:
pip install EasyROI
from EasyROI import EasyROI
roi_helper = EasyROI()
roi = roi_helper.draw_rectangle(frame, quantity=2)
Related
I'm in the process of developing a Flask Python application that's able to find a logo within different background images. The goal is to have a solution that states "yes, the logo is in the background", or "no, it doesn't look like the logo is in the background". I'm utilizing the SIFT package to match keypoints between the logo and the image with the logo in the background.
I want to figure out how I can write an IF statement that's able to deliver the message above depending on the keypoints. Is there anyone that can give me guidance on the first steps of doing this? I'll attach the code to this message (note that the function should have an indent there):
#app.route('/identify/<filename>')
def identify(filename):
""" After uploading the image,
show the identification of the uploaded image
"""
# TODO: Logic to load the uploaded image filename and identify other images
image_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
image_url = url_for('images', filename=filename)
background_image = cv2.imread(image_path)
background_image = cv2.cvtColor(background_image, cv2.COLOR_BGR2RGB)
#still need to figure out how to load a second photo of the user's choice
#loading in the photo to find within the uploaded photo
logo = cv2.imread("chevy-open-road-logo-300.png")
logo = cv2.cvtColor(logo, cv2.COLOR_BGR2RGB)
#creating a copy and implementing a SIFT Image Matching method
background_image_copy = background_image.copy()
#sift
sift = cv2.xfeatures2d.SIFT_create()
background_keypoints, background_descriptors = sift.detectAndCompute(background_image_copy, None)
logo_keypoints, logo_descriptors = sift.detectAndCompute(logo, None)
#feature matching
bf = cv2.BFMatcher(cv2.NORM_L1, crossCheck=True)
matches = bf.match(background_descriptors,logo_descriptors)
matches = sorted(matches, key = lambda x:x.distance)
#img = BytesIO()
image_match = cv2.drawMatches(background_image_copy, background_keypoints, logo, logo_keypoints, matches[:45], logo, flags=2)
plt.imshow(image_match), plt.show()
'''
#Converting the plot to PNG image
plt.savefig(img, format='png', bbox_inches='tight')
img.seek(0)
plot_url = base64.b64encode(img.getvalue()).decode()
'''
'''
#Printing the number of keypoints detected in the training image
x = str(len(background_keypoints))
#Printing the number of keypoints detected in the logo image
y = str((len(logo_keypoints)))
# Printing total number of matching points between the training and logo images
z = str((len(matches)))
'''
return render_template('identify.html',
image = image_url#, plot_url=plot_url
#x=x, y=y, z=z
)
I'm trying to make a little weather forecast program which gives you an image with an overview of the weather in python
To get the weather, I'm using openweathermap and it works ok for me, but for the image I'm using PIL to paste the weather icon, but for some reason there's a part of it that's not being pasted, here you can see what the icon should be: https://openweathermap.org/img/wn/04n#2x.png, and here's how it appeared in the image that came out of my script:
Here's the part of the code that generates the image:
def drawImage(d):
img=PIL.Image.open("base.png")
url=f"https://openweathermap.org/img/wn/{d['icon']}#2x.png"
weatherIcon=Image.open(requests.get(url, stream=True).raw)
print(url)
img.paste(weatherIcon, (00, 10))
now=datetime.now()
name="boards/"+now.strftime('%d_%m_%Y_%H_%M_%S')+".png"
img.save(name)
return name
Some notes on this code:
The base.png is just a 720x720 blank image
The d that gets passed in is a dictionary with all the information, but here it only needs the icon, so I'll give this example: {"icon": "04n"}
I got the URL for the image from the website of OpenWeatherMap, see documentation: https://openweathermap.org/weather-conditions
This is happening because the icon image you download has transparency (an alpha channel). To remove that, you can use this answer.
I've simplified it slightly, define the following function:
def remove_transparency(im, bg_colour=(255, 255, 255)):
if im.mode in ('RGBA', 'LA') or (im.mode == 'P' and 'transparency' in im.info):
alpha = im.getchannel('A')
bg = Image.new("RGBA", im.size, bg_colour + (255,))
bg.paste(im, mask=alpha)
return bg
else:
return im
and call it in your code:
weatherIcon=Image.open(requests.get(url, stream=True).raw)
print(url)
weatherIcon = remove_transparency(weatherIcon)
img.paste(weatherIcon, (00, 10))
You might want to adjust that bg_colour parameter.
I use python 3.8 and Opencv in Linux.
I have several buttons that have stacked horizontally. How can I arrange them as I like (e.g., in a grid way?)
Is it possible to show some icons for each of the buttons?
Is it possible to make the fonts of the buttons bar larger?
Part of my script: (any suggestion to make my script better is appreciated)
if __name__== "__main__":
Folder_name = "male"
data_path = "path/to/images"
data_path = os.path.join(data_path, Folder_name)
all_imgs_path = glob.glob("{}/*.jpg".format(data_path))
all_imgs_path = sorted(all_imgs_path)
annot = annotation_tool(nof_imgs=len(all_imgs_path))
for index, im_dir in enumerate(all_imgs_path):
annot[index] = im_dir
item_path = "guid.jpg"
img = cv2.imread(item_path)
img_name = item_path.split("/")[-1]
cv2.imshow("{}".format(img_name), img)
cv2.createButton('Next', annot.Next, ["Next Image"])
cv2.createButton('Back', annot.Back, ["Previous Image"])
cv2.createButton('Submit', annot.Submit, ["Submit"])
# there are many of these buttons
UB_Tshirt = cv2.createButton("UB_Tshirt", annot.checkbox, "UB_Tshirt", 1, 0)
UB_Shirt = cv2.createButton("UB_Shirt", annot.checkbox, "UB_Shirt", 1, 0)
UB_Coat = cv2.createButton("UB_Coat", annot.checkbox, "UB_Coat", 1, 0)
cv2.waitKey(0)
print("end")
Edit:
As you see in the image, the buttons bar is very long and goes out of the screen. I would like to create a button pad that is squared.
This isn't a complete answer, but in regards to button arrangement, you have a little control using 'cv2.QT_NEW_BUTTONBAR'.
There's further detail here: https://docs.opencv.org/4.x/dc/d46/group__highgui__qt.html#gad15c7adb377e778dc907c0e318be193e
I'm trying to save a captured 640x480 RGB image with NAO's front camera to my computer. I'm using python and PIL to do so. Unfortunately, the image just won't save on my computer, no matter what image type or path I use for the parameters of the Image.save()- Method. the image created with PIL contains valid RGB-information though. Here's my code sample from choregraphe:
import Image
def onInput_onStart(self):
cam_input = ALProxy("ALVideoDevice")
nameId = cam_input.subscribeCamera("Test_Cam", 1, 2, 13, 20)
image = cam_input.getImageRemote(nameId) #captures an image
w = image[0] #get the image width
h = image[1] #get the image height
pixel_array = image[6] #contains the image data
result = Image.fromstring("RGB", (w, h), pixel_array)
#the following line doesnt work
result.save("C:\Users\Claudia\Desktop\NAO\Bilder\test.png", "PNG")
cam_input.releaseImage(nameId)
cam_input.unsubscribe(nameId)
pass
Thank you so much for your help in advance!
- a frustrated student
In the comment, you say the code is pasted from choregraphe, so I guess you launch it using choregraphe.
If so, then the code is injected into your robot then started.
So your image is saved to the NAO hard drive and I guess your robot doesn't have a folder named: "C:\Users\Claudia\Desktop\NAO\Bilder\test.png".
So change the path to "/home/nao/test.png", start your code, then log into your NAO using putty or browse folder using winscp (as it looks like you're using windows).
And you should see your image-file.
In order for your code to run correctly it needs to be properly indented. Your code should look like this:
import Image
def onInput_onStart(self):
cam_input = ALProxy("ALVideoDevice")
nameId = cam_input.subscribeCamera("Test_Cam", 1, 2, 13, 20)
image = cam_input.getImageRemote(nameId) #captures an image
w = image[0] #get the image width
h = image[1] #get the image height
pixel_array = image[6] #contains the image data
...
Make sure to indent everything that's inside the def onInput_onStart(self): method.
Sorry for the late response, but it maybe helpful for someone. You should try it with naoqi. Here is the documentation for retriving images
http://doc.aldebaran.com/2-4/dev/python/examples/vision/get_image.html
The original code was not working for me so I made some tweeks.
parser = argparse.ArgumentParser()
parser.add_argument("--ip", type=str, default="nao.local.",
help="Robot IP address. On robot or Local Naoqi: use
'nao.local.'.")
parser.add_argument("--port", type=int, default=9559,
help="Naoqi port number")
args = parser.parse_args()
session = qi.Session()
try:
session.connect("tcp://" + args.ip + ":" + str(args.port))
except RuntimeError:
pass
"""
First get an image, then show it on the screen with PIL.
"""
# Get the service ALVideoDevice.
video_service = session.service("ALVideoDevice")
resolution = 2 # VGA
colorSpace = 11 # RGB
videoClient = video_service.subscribe("python_client",0,3,13,1)
t0 = time.time()
# Get a camera image.
# image[6] contains the image data passed as an array of ASCII chars.
naoImage = video_service.getImageRemote(videoClient)
t1 = time.time()
# Time the image transfer.
print ("acquisition delay ", t1 - t0)
#video_service.unsubscribe(videoClient)
# Now we work with the image returned and save it as a PNG using ImageDraw
# package.
# Get the image size and pixel array.
imageWidth = naoImage[0]
imageHeight = naoImage[1]
array = naoImage[6]
image_string = str(bytearray(array))
# Create a PIL Image from our pixel array.
im = Image.fromstring("RGB", (imageWidth, imageHeight), image_string)
# Save the image.
im.save("C:\\Users\\Lenovo\\Desktop\\PROJEKTI\\python2-
connect4\\camImage.png", "PNG")
Be careful to use Python 2.7.
The code runs on your computer not the NAO robot!
Imagine a red circle with a black dropshadow that fades away on top of a fully transparent background. When I open and resave the image with PIL the background remains fully transparent but the dropshadow becomes full black.
The problem appears without even altering the image:
image = Image.open('input.png')
image = image.convert('RGBA')
image.save('output.png')
I want to keep the image looking exactly as the original so that I can crop or resize it.
EDIT: Here's a PNG that demonstrates the effect. It was converted to 8bit by using PNGNQ.
When using the above Python code it comes out as the following:
It looks like PIL currently doesn't support full alpha for PNG8.
There is a patch here for read-only support: http://mail.python.org/pipermail/image-sig/2010-October/006533.html
If you're feeling naughty, you could monkeypatch PIL:
from PIL import Image, ImageFile, PngImagePlugin
def patched_chunk_tRNS(self, pos, len):
i16 = PngImagePlugin.i16
s = ImageFile._safe_read(self.fp, len)
if self.im_mode == "P":
self.im_info["transparency"] = map(ord, s)
elif self.im_mode == "L":
self.im_info["transparency"] = i16(s)
elif self.im_mode == "RGB":
self.im_info["transparency"] = i16(s), i16(s[2:]), i16(s[4:])
return s
PngImagePlugin.PngStream.chunk_tRNS = patched_chunk_tRNS
def patched_load(self):
if self.im and self.palette and self.palette.dirty:
apply(self.im.putpalette, self.palette.getdata())
self.palette.dirty = 0
self.palette.rawmode = None
try:
trans = self.info["transparency"]
except KeyError:
self.palette.mode = "RGB"
else:
try:
for i, a in enumerate(trans):
self.im.putpalettealpha(i, a)
except TypeError:
self.im.putpalettealpha(trans, 0)
self.palette.mode = "RGBA"
if self.im:
return self.im.pixel_access(self.readonly)
Image.Image.load = patched_load
Image.open('kHrY6.png').convert('RGBA').save('kHrY6-out.png')
I think that the problem has been somewhat resolved, but is it possible that you need to set the depth of the alpha channel?