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making an F1 application where users can type in a driver from the current grid [supported via autofill/suggestions], and then API fetches relevant stats
The issue I'm having is that I want the listbox to appear over another frame (called left_frame). However, what this does is that the listbox goes under left_frame , and not over it. Any thoughts of how to make it appear over the frame?
some approaches that I tried:
used .lift(), but .lift() only seems to work when it's relative to objects in the same frame
since I currently use .grid and placed the listbox in the root frame, I initially tried to put it in top_frame, but it then expands the top_frame. Since I have positioned all frames using .place(), I don't think I can use propagate(False) (I tried it , didn't work)
Here's a picture of the issues
Here's my code so far:
#import necessary modules
from tkinter import *
from tkinter import ttk
from PIL import ImageTk, Image
from tkinter import messagebox
import requests
import json
#set up main window components
root = Tk()
root.title("F1 Desktop Application")
root.geometry("500x600")
root.configure(bg="white")
#since same directory, can just use filename
root.iconbitmap("formula1_logo.ico")
#images
#creating canvas for image to go into
#canvas_f1_logo = Canvas(top_frame, width = 5, height = 5)
#canvas.grid(row = 0, column = 1)
#acquire image
#formula1_logo = ImageTk.PhotoImage(Image.open("formula1_logo.png"))
#resize image
#resized_formula1_logo = formula1_logo.resize((3,3), Image.ANTIALIAS)
#new_formula1_logo = ImageTK.PhotoImage(resized_formula1_logo)
#canvas.create_image(5,5, anchor = NW, image = new_formula1_logo)
#functions
#generate 2022 drivers-list [can scale to drivers-list by changing the]
drivers_list_request = requests.get("http://ergast.com/api/f1/2022/drivers.json")
#initialize empty-list
drivers_list = []
drivers_list_object = json.loads(drivers_list_request.content)
for elements in drivers_list_object["MRData"]["DriverTable"]["Drivers"]:
drivers_list.append(elements["givenName"] + " " + elements["familyName"])
#set up frames [main frames, can put frames within frames if needed]
#frame for search bar + magnifying glass
top_frame = LabelFrame(root, padx = 80, pady = 15)
top_frame.place(relx = 0.5, rely = 0.2, anchor = CENTER)
header_label = Label(top_frame, text = "F1 2022 Drivers App", pady = 20, font = ("Arial bold",14))
header_label.grid(row = 0, column = 0, pady = 2 )
search_button = Button(top_frame, text = "search", padx = 2, pady = 2)
search_button.grid(row = 1, column = 1)
# Update the Entry widget with the selected item in list
def check(e):
v= entry.get()
if v=='':
hide_button(menu)
else:
data=[]
for item in drivers_list:
if v.lower() in item.lower():
data.append(item)
update(data)
show_button(menu)
def update(data):
# Clear the Combobox
menu.delete(0, END)
# Add values to the combobox
for value in data:
menu.insert(END,value)
def fillout(event):
try:
entry.delete(0,END)
entry.insert(0,menu.get(menu.curselection()))
#handle a complete deletion of entry-box via cursor double tap
except:
pass
def hide_button(widget):
widget.grid_remove()
def show_button(widget):
widget.grid()
# Create an Entry widget
entry= Entry(top_frame)
entry.grid(row = 1, column = 0)
entry.bind('<KeyRelease>',check)
# Create a Listbox widget to display the list of items
menu= Listbox(root)
menu.grid(row = 2, column = 0, padx = 165, pady = 165)
menu.bind("<<ListboxSelect>>",fillout)
menu.lift()
# Add values to our combobox
hide_button(menu)
left_frame = LabelFrame(root, padx = 30, pady = 30)
left_frame.place(relx = 0.24, rely = 0.5, anchor = CENTER)
bottom_left_frame = LabelFrame(root, padx = 30, pady = 30)
bottom_left_frame.place(relx = 0.24, rely = 0.82, anchor = CENTER)
bottom_right_frame = LabelFrame(root, padx = 30, pady = 30)
bottom_right_frame.place(relx = 0.6, rely = 0.82)
basic_info = Label(left_frame, text = "Basic Info ", font = ("Arial bold",14))
basic_info.grid(row = 0, column = 0, pady = 3)
full_name = Label(left_frame, text = "Full Name : ")
full_name.grid(row = 1, column = 0, pady = 2)
driver_code = Label(left_frame, text = "Driver Code : ")
driver_code.grid(row = 2, column = 0, pady = 2)
nationality = Label(left_frame, text = "Nationality : ")
nationality.grid(row = 3, column = 0, pady = 2)
F1_career = Label(bottom_left_frame, text = "F1 Career ", font = ("Arial bold",14))
F1_career.grid(row = 0, column = 0, pady = 3)
wins = Label(bottom_left_frame, text = "Wins :")
wins.grid(row = 1, column = 0, pady = 2)
poles = Label(bottom_left_frame, text = "Poles :")
poles.grid(row = 2, column = 0, pady = 2)
drivers_championships = Label(bottom_left_frame, text = "Championships :")
drivers_championships.grid(row = 3, column = 0 , pady = 2)
F1_22_stats = Label(bottom_right_frame, text = "F1 22 Stats", font = ("Arial bold",14))
F1_22_stats.grid(row = 0, column = 0, pady = 3)
root.mainloop()
would appreciate the help!
How I can get actual coordinates of Landsat image corners (see image to understand) ?
From metadata file (..._MTL.txt) I can get coordinates of red corners, but I need to get coordinates of green corners.
I work with GeoTIFF files using GDAL.
I need to get correct latitude and longitude of green points.
Can I do it using python3?
Thanks for help
Metadata file
GROUP = L1_METADATA_FILE
GROUP = METADATA_FILE_INFO
ORIGIN = "Image courtesy of the U.S. Geological Survey"
REQUEST_ID = "9991103150002_00325"
PRODUCT_CREATION_TIME = 2011-03-16T20:14:24Z
STATION_ID = "EDC"
LANDSAT5_XBAND = "1"
GROUND_STATION = "IKR"
LPS_PROCESSOR_NUMBER = 0
DATEHOUR_CONTACT_PERIOD = "1016604"
SUBINTERVAL_NUMBER = "01"
END_GROUP = METADATA_FILE_INFO
GROUP = PRODUCT_METADATA
PRODUCT_TYPE = "L1T"
ELEVATION_SOURCE = "GLS2000"
PROCESSING_SOFTWARE = "LPGS_11.3.0"
EPHEMERIS_TYPE = "DEFINITIVE"
SPACECRAFT_ID = "Landsat5"
SENSOR_ID = "TM"
SENSOR_MODE = "BUMPER"
ACQUISITION_DATE = 2010-06-15
SCENE_CENTER_SCAN_TIME = 04:57:44.2830500Z
WRS_PATH = 145
STARTING_ROW = 26
ENDING_ROW = 26
BAND_COMBINATION = "1234567"
PRODUCT_UL_CORNER_LAT = 49.8314223
PRODUCT_UL_CORNER_LON = 84.0018859
PRODUCT_UR_CORNER_LAT = 49.8694055
PRODUCT_UR_CORNER_LON = 87.4313889
PRODUCT_LL_CORNER_LAT = 47.8261840
PRODUCT_LL_CORNER_LON = 84.1192898
PRODUCT_LR_CORNER_LAT = 47.8615913
PRODUCT_LR_CORNER_LON = 87.4144676
PRODUCT_UL_CORNER_MAPX = 284400.000
PRODUCT_UL_CORNER_MAPY = 5524200.000
PRODUCT_UR_CORNER_MAPX = 531000.000
PRODUCT_UR_CORNER_MAPY = 5524200.000
PRODUCT_LL_CORNER_MAPX = 284400.000
PRODUCT_LL_CORNER_MAPY = 5301000.000
PRODUCT_LR_CORNER_MAPX = 531000.000
PRODUCT_LR_CORNER_MAPY = 5301000.000
PRODUCT_SAMPLES_REF = 8221
PRODUCT_LINES_REF = 7441
PRODUCT_SAMPLES_THM = 4111
PRODUCT_LINES_THM = 3721
BAND1_FILE_NAME = "L5145026_02620100615_B10.TIF"
BAND2_FILE_NAME = "L5145026_02620100615_B20.TIF"
BAND3_FILE_NAME = "L5145026_02620100615_B30.TIF"
BAND4_FILE_NAME = "L5145026_02620100615_B40.TIF"
BAND5_FILE_NAME = "L5145026_02620100615_B50.TIF"
BAND6_FILE_NAME = "L5145026_02620100615_B60.TIF"
BAND7_FILE_NAME = "L5145026_02620100615_B70.TIF"
GCP_FILE_NAME = "L5145026_02620100615_GCP.txt"
METADATA_L1_FILE_NAME = "L5145026_02620100615_MTL.txt"
CPF_FILE_NAME = "L5CPF20100401_20100630_09"
END_GROUP = PRODUCT_METADATA
GROUP = MIN_MAX_RADIANCE
LMAX_BAND1 = 193.000
LMIN_BAND1 = -1.520
LMAX_BAND2 = 365.000
LMIN_BAND2 = -2.840
LMAX_BAND3 = 264.000
LMIN_BAND3 = -1.170
LMAX_BAND4 = 221.000
LMIN_BAND4 = -1.510
LMAX_BAND5 = 30.200
LMIN_BAND5 = -0.370
LMAX_BAND6 = 15.303
LMIN_BAND6 = 1.238
LMAX_BAND7 = 16.500
LMIN_BAND7 = -0.150
END_GROUP = MIN_MAX_RADIANCE
GROUP = MIN_MAX_PIXEL_VALUE
QCALMAX_BAND1 = 255.0
QCALMIN_BAND1 = 1.0
QCALMAX_BAND2 = 255.0
QCALMIN_BAND2 = 1.0
QCALMAX_BAND3 = 255.0
QCALMIN_BAND3 = 1.0
QCALMAX_BAND4 = 255.0
QCALMIN_BAND4 = 1.0
QCALMAX_BAND5 = 255.0
QCALMIN_BAND5 = 1.0
QCALMAX_BAND6 = 255.0
QCALMIN_BAND6 = 1.0
QCALMAX_BAND7 = 255.0
QCALMIN_BAND7 = 1.0
END_GROUP = MIN_MAX_PIXEL_VALUE
GROUP = PRODUCT_PARAMETERS
CORRECTION_METHOD_GAIN_BAND1 = "CPF"
CORRECTION_METHOD_GAIN_BAND2 = "CPF"
CORRECTION_METHOD_GAIN_BAND3 = "CPF"
CORRECTION_METHOD_GAIN_BAND4 = "CPF"
CORRECTION_METHOD_GAIN_BAND5 = "CPF"
CORRECTION_METHOD_GAIN_BAND6 = "IC"
CORRECTION_METHOD_GAIN_BAND7 = "CPF"
CORRECTION_METHOD_BIAS = "IC"
SUN_AZIMUTH = 141.2669762
SUN_ELEVATION = 59.9909680
OUTPUT_FORMAT = "GEOTIFF"
END_GROUP = PRODUCT_PARAMETERS
GROUP = CORRECTIONS_APPLIED
STRIPING_BAND1 = "NONE"
STRIPING_BAND2 = "NONE"
STRIPING_BAND3 = "NONE"
STRIPING_BAND4 = "NONE"
STRIPING_BAND5 = "NONE"
STRIPING_BAND6 = "NONE"
STRIPING_BAND7 = "NONE"
BANDING = "N"
COHERENT_NOISE = "N"
MEMORY_EFFECT = "Y"
SCAN_CORRELATED_SHIFT = "Y"
INOPERABLE_DETECTORS = "N"
DROPPED_LINES = "N"
END_GROUP = CORRECTIONS_APPLIED
GROUP = PROJECTION_PARAMETERS
REFERENCE_DATUM = "WGS84"
REFERENCE_ELLIPSOID = "WGS84"
GRID_CELL_SIZE_THM = 60.000
GRID_CELL_SIZE_REF = 30.000
ORIENTATION = "NUP"
RESAMPLING_OPTION = "CC"
MAP_PROJECTION = "UTM"
END_GROUP = PROJECTION_PARAMETERS
GROUP = UTM_PARAMETERS
ZONE_NUMBER = 45
END_GROUP = UTM_PARAMETERS
END_GROUP = L1_METADATA_FILE
END
You might first find the contour with the biggest area. Then try some algorithm to find the points you want. It seems that the satellite picture in the image is not a perfect rectangle, so you can't fit a rectangle on it using OpenCV's built-in methods.
You should try something like that:
import cv2
import numpy as np
img = cv2.imread('z_edited.jpg')
imgray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(imgray, (11, 11), 0)
ret, thresh = cv2.threshold(blurred, 27, 255, 0)
cnts, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
max_area = 0
max_area_index = 0
for i, cnt in enumerate(cnts):
area = cv2.contourArea(cnt)
if area > max_area:
max_area = area
max_area_index = i
x_min = np.min(cnts[max_area_index][:, 0, 0])
x_max = np.max(cnts[max_area_index][:, 0, 0])
y_min = np.min(cnts[max_area_index][:, 0, 1])
y_max = np.max(cnts[max_area_index][:, 0, 1])
(x_left, y_left) = (x_min, cnts[max_area_index][np.max(np.where(cnts[max_area_index][:, 0, 0] == x_min)), 0, 1])
(x_right, y_right) = (x_max, cnts[max_area_index][np.max(np.where(cnts[max_area_index][:, 0, 0] == x_max)), 0, 1])
(x_down, y_down) = (cnts[max_area_index][np.max(np.where(cnts[max_area_index][:, 0, 1] == y_max)), 0, 0], y_max)
(x_top, y_top) = (cnts[max_area_index][np.max(np.where(cnts[max_area_index][:, 0, 1] == y_min)), 0, 0], y_min)
cv2.circle(img, (x_left, y_left), 10, (0, 0, 255), thickness=8)
cv2.circle(img, (x_right, y_right), 10, (0, 0, 255), thickness=8)
cv2.circle(img, (x_down, y_down), 10, (0, 0, 255), thickness=8)
cv2.circle(img, (x_top, y_top), 10, (0, 0, 255), thickness=8)
# cv2.drawContours(img, cnts, max_area_index, (0, 255, 0), 2)
cv2.namedWindow('s', cv2.WINDOW_NORMAL)
cv2.imshow('s', img)
cv2.waitKey(0)
And the result looks like:
Using this code you can find the coordinates of the corners of the satellite picture inside the image(red points).
Also need to say I have assumed that your satellite picture background is completely black(the image you have uploaded, has a thin gray strip around the whole image).
This is my python script:
while True:
text = ""
img = cam.read()[1]
img = cv2.flip(img, 1)
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
dst = cv2.calcBackProject([imgHSV], [0, 1], hist, [0, 180, 0, 256], 1)
disc = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(10,10))
cv2.filter2D(dst,-1,disc,dst)
blur = cv2.GaussianBlur(dst, (11,11), 0)
blur = cv2.medianBlur(blur, 15)
thresh = cv2.threshold(blur,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]
thresh = cv2.merge((thresh,thresh,thresh))
thresh = cv2.cvtColor(thresh, cv2.COLOR_BGR2GRAY)
thresh = thresh[y:y+h, x:x+w]
contours = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[1]
if len(contours) > 0:
contour = max(contours, key = cv2.contourArea)
if cv2.contourArea(contour) > 10000:
x1, y1, w1, h1 = cv2.boundingRect(contour)
save_img = thresh[y1:y1+h1, x1:x1+w1]
This code works properly on another system but while I run it in my system,
it shows the following error:
cv2.error: OpenCV(4.0.0) /io/opencv/modules/imgproc/src/shapedescr.cpp:272: error: (-215:Assertion failed) npoints >= 0 && (depth == CV_32F || depth == CV_32S) in function 'contourArea'
Which can be caused by the following script:
contour = max(contours, key = cv2.contourArea)
I am using ubuntu 18.02 and opencv 4.0...
This is as part of our project, please help.
This problem is occurring because cv2.findContours has changed from V3.X to V4.0 in opencv.
So in V3.X it used to be
findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> image, contours, hierarchy
Three objects returned.
and V4.0
findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> contours, hierarchy
Two objects returned.
So you code would be
contours = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[0]
if you intend to get contours.
I am working on an example from an older book, so far I have the program working but the color adjustment only works for the third "blue" slider. I tried troubleshooting by changing the range() found after get_pressed(). I changed it from 3 to 2 to 1 and they all behaved the same. I don't understand, I was thinking it would move with the changes.
import pygame as pg
from pygame.locals import *
from sys import exit
pg.init()
WIDTH, HEIGHT = 800, 600
screen = pg.display.set_mode((WIDTH, HEIGHT), 0, 32)
color = [127, 127, 127]
# Creates an image with smooth gradients
def createScales(height):
redScaleSurface = pg.surface.Surface((WIDTH, height))
greenScaleSurface = pg.surface.Surface((WIDTH,height))
blueScaleSurface = pg.surface.Surface((WIDTH,height))
for x in range(WIDTH):
c =int((x/(WIDTH-1.))*255.)
red = (c, 0, 0)
green = (0, c, 0)
blue = (0, 0, c)
line_rect = Rect(x, 0, 1, height)
pg.draw.rect(redScaleSurface, red, line_rect)
pg.draw.rect(greenScaleSurface, green, line_rect)
pg.draw.rect(blueScaleSurface, blue, line_rect)
return redScaleSurface, greenScaleSurface, blueScaleSurface
redScale, greenScale, blueScale = createScales(80)
while True:
for event in pg.event.get():
if event.type == pg.QUIT:
pg.quit()
exit()
screen.fill((0, 0, 0))
# Draw the scales to the screen
screen.blit(redScale, (0, 00))
screen.blit(greenScale, (0, 80))
screen.blit(blueScale, (0, 160))
x, y = pg.mouse.get_pos()
# If the mouse was pressed on one of the sliders, adjust the color component
if pg.mouse.get_pressed()[0]:
for compononent in range(3):
if y > component*80 and y < (component+1)*80:
color[component] = int((x/(WIDTH-1.))*255.)
pg.display.set_caption("PyGame Color Test - " + str(tuple(color)))
# Draw a circle for each slider to represent the curret setting
for component in range(3):
pos = ( int((color[component]/255.)*(WIDTH-1)), component*80+40 )
pg.draw.circle(screen, (255, 255, 255), pos, 20)
pg.draw.rect(screen, tuple(color), (0, 240, WIDTH, HEIGHT/2))
pg.display.update()
On line 49, I made a typo and wrote component as compononent. Once fixed, I now have a neat interactive program for demonstrating computers' additive color model!
I am trying to draw contours on a specific part of a slice of a MRI. The code is as follows:
epi_img = nib.load('G:\BTech Project Dataset\MICCAI_BraTS17_Data_Training\HGG\Brats17_CBICA_AAL_1\Brats17_CBICA_AAL_1_t2.nii.gz')
epi_img_data = epi_img.get_data()
slice_2 = epi_img_data[:, :, 78]
###Selection of the best region for tumor incidence
se1 = cv2.getStructuringElement(cv2.MORPH_RECT, (7,7))
se2 = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
###Performing Closing Operation
closing_mask = cv2.morphologyEx(thresholded2, cv2.MORPH_CLOSE, se1)
###Performing Opening Operation
opening_mask = cv2.morphologyEx(closing_mask, cv2.MORPH_OPEN, se2)
### find contours in the edge map
cnts = cv2.findContours(thresholded2.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
cnts=np.array(cnts)
cv2.drawContours(slice_2,cnts, -1, (0, 255, 0), 2)
I referred to similar other questions here and applied their suggested solution as well.
Still, I keep getting the same error