Is there a way to guarantee a certain number of lines detected with cv2.HoughLines()?

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• Python File Tagging System does not retrieve nested dictionaries in dictionary

  I am building a file tagging system using Python. The idea is simple. Given a directory of files (and files within subdirectories), I want to filter them out using a filter input and tag those files with a word or a phrase.

  If I got the following contents in my current directory:

  data/
     budget.xls
     world_building_budget.txt
  a.txt
  b.exe
  hello_world.dat
  world_builder.spec
  

  and I execute the following command in the shell:

  py -3 tag_tool.py -filter=world -tag="World-Building Tool"
  

  My output will be:

  These files were tagged with "World-Building Tool":
  data/ world_building_budget.txt
  hello_world.dat
  world_builder.spec
  

  My current output isn't exactly like this but basically, I am converting all files and files within subdirectories into a single dictionary like this:

  def fs_tree_to_dict(path_):
      file_token = ''
      for root, dirs, files in os.walk(path_):
          tree = {d: fs_tree_to_dict(os.path.join(root, d)) for d in dirs}
          tree.update({f: file_token for f in files})
          return tree
  

  Right now, my dictionary looks like this: key:''.

  In the following function, I am turning the empty values '' into empty lists (to hold my tags):

  def empty_str_to_list(d):
      for k,v in d.items():
          if v == '':
              d[k] = []
          elif isinstance(v, dict):
              empty_str_to_list(v)
  

  When I run my entire code, this is my output:

  hello_world.dat ['World-Building Tool']
  world_builder.spec ['World-Building Tool']
  

  But it does not see data/world_building_budget.txt. This is the full dictionary:

  {'data': {'world_building_budget.txt': []},  
  'a.txt': [],
  'hello_world.dat': [], 
  'b.exe': [], 
  'world_builder.spec': []}
  
  

  This is my full code:

  import os, argparse
  
  
  def fs_tree_to_dict(path_):
      file_token = ''
      for root, dirs, files in os.walk(path_):
          tree = {d: fs_tree_to_dict(os.path.join(root, d)) for d in dirs}
          tree.update({f: file_token for f in files})
          return tree
  
  
  def empty_str_to_list(d):
      for k, v in d.items():
          if v == '':
              d[k] = []
          elif isinstance(v, dict):
              empty_str_to_list(v)
  
  
  parser = argparse.ArgumentParser(description="Just an example", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
  
  parser.add_argument("--filter", action="store", help="keyword to filter files")
  parser.add_argument("--tag", action="store", help="a tag phrase to attach to a file")
  parser.add_argument("--get_tagged", action="store", help="retrieve files matching an existing tag")
  
  args = parser.parse_args()
  
  filter = args.filter
  tag = args.tag
  get_tagged = args.get_tagged
  current_dir = os.getcwd()
  
  files_dict = fs_tree_to_dict(current_dir)
  empty_str_to_list(files_dict)
  
  for k, v in files_dict.items():
      if filter in k:
          if v == []:
              v.append(tag)
              print(k, v)
  
          elif isinstance(v, dict):
              empty_str_to_list(v)
  
      if get_tagged in v:
          print(k, v)
  
• Actaully i am working on a project and in it, it is showing no module name pip_internal plz help me for the same. I am using pycharm(conda interpreter

   File "C:\Users\pjain\AppData\Local\Programs\Python\Python310\lib\runpy.py", line 196, in _run_module_as_main
      return _run_code(code, main_globals, None,
    File "C:\Users\pjain\AppData\Local\Programs\Python\Python310\lib\runpy.py", line 86, in _run_code
      exec(code, run_globals)
    File "C:\Users\pjain\AppData\Local\Programs\Python\Python310\Scripts\pip.exe\__main__.py", line 4, in <module>
    File "C:\Users\pjain\AppData\Local\Programs\Python\Python310\lib\site-packages\pip\_internal\__init__.py", line 4, in <module>
      from pip_internal.utils import _log
  

  I am using pycharm with conda interpreter.

  
• Looping the function if the input is not string

  I'm new to python (first of all) I have a homework to do a function about checking if an item exists in a dictionary or not.

  inventory = {"apple" : 50, "orange" : 50, "pineapple" : 70, "strawberry" : 30}
  
  def check_item():
      x = input("Enter the fruit's name: ")
      if not x.isalpha():
          print("Error! You need to type the name of the fruit")
      elif x in inventory:
          print("Fruit found:", x)
          print("Inventory available:", inventory[x],"KG")
      else:
          print("Fruit not found")
  check_item()
  

  I want the function to loop again only if the input written is not string. I've tried to type return Under print("Error! You need to type the name of the fruit") but didn't work. Help
• How To set the size of image more than default value in OpenCV

  1. What is the default frame size of opencv image streaming frame ?

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• How to read grayscale img from a video with OpenCV?

  I read all pictures from my pic directory and then convert them each to gray-scale with canny edge detections before writing it all to a video.

  But, when I use my video software to play it, it shows a green background, and I can't read video frames from it. Could someone show me how to solve it?

  Sample code

  import numpy as np
  import cv2 as cv
  import matplotlib.pyplot as plt
  
  fourcc = cv.VideoWriter_fourcc(*"I420")
  out = cv.VideoWriter("t2.avi", fourcc, 1, (640, 480), 0)
  for pic in glob.glob1("./pic/", "A*"):
      img = cv.imread(f"./pic/{pic}", -1)
      
      edge = cv.Canny(img, 100, 200)
      edge = cv.resize(edge, (640, 480))
      out.write(edge)
  
  out.release()
  
  # Cant read video frame here:
  cap = cv.VideoCapture("t2.avi")
  ret, frame = cap.read()
  if ret:
      plt.imshow(frame)
  else:
      print("end")
      cap.release()
  

  Video plays with green background
• Image Background Remover Using Python

  I want to make Image Background Remover Using Python But I do not know how much data It will take and time to reach the accuracy of remove.bg I'm using U-2-Net Ai models https://github.com/xuebinqin/U-2-Net/ Some results are same but not every result is as good enough as remove.bg In a rating I would tell my app as 2/5 and remove.bg as 4/5 Please tell me How can I achieve accuracy like remove.bg Any help or suggestions are appreciated. Thanks
• Android app data analysis over supermarket deals images

  For an university project i need to create an Android application that collects and aggregates data from various supermarket flyers in order to filter deals by user inserted details.

  As inspiration i am looking at commercial applications and i came across Shopfully that have a really interesting feature.

  Their app is able to recognize the images of the flyers placing a floating plus button on each product.

  Example:

  

  If the user press on the plus floating button product details are showed (price, discount amount):

  

  I am wondering how they made that? I imagine that they use some sort of image recognition to process flyers and an OCR text recognition to parse the text.

  Would any of you have any ideas on how I might be able to reproduce this feature?
• The edge module has not been pre-compiled for node.js version v14.18.1. You must build a custom version of edge.node. getting this error

  { "name": "electron-js", "version": "0.0.0", "description": "ElectronJs", "main": "app.js", "scripts": { "start": "electron ." }, "author": { "name": "Ralph" }, "dependencies": { "edge": "^7.10.1", "edge-js": "^16.6.0", "electron": "^1.6.2", "electron-edge": "6.5.5", "jquery": "3.2.1" }, "devDependencies": { "@types/electron": "1.4.34", "electron-packager": "^15.5.1", "electron-prebuilt": "^1.4.13" } }

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• why the hough transform can't find the line at right-below corner of the image?

  I am trying use hough transform to find the edge, the following image's right-below corner line can't be found. why?

  My code

  BW = imread("edge/30.1.tif");
  [H,theta,rho] = hough(BW);
  imshow(imadjust(rescale(H)),[],...
         'XData',theta,...
         'YData',rho,...
         'InitialMagnification','fit');
  xlabel('\theta (degrees)')
  ylabel('\rho')
  axis on
  axis normal 
  hold on
  colormap(gca,hot);  
  P = houghpeaks(H,5,'threshold',ceil(0.3*max(H(:))));
  x = theta(P(:,2));
  y = rho(P(:,1));
  plot(x,y,'s','color','black');
  
  lines = houghlines(BW,theta,rho,P,'FillGap',5,'MinLength',7);
  
  figure, imshow(BW), hold on
  max_len = 0;
  for k = 1:length(lines)
     xy = [lines(k).point1; lines(k).point2];
     plot(xy(:,1),xy(:,2),'LineWidth',2,'Color','green');
  
     % Plot beginnings and ends of lines
     plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','yellow');
     plot(xy(2,1),xy(2,2),'x','LineWidth',2,'Color','red');
  
     % Determine the endpoints of the longest line segment
     len = norm(lines(k).point1 - lines(k).point2);
     if ( len > max_len)
        max_len = len;
        xy_long = xy;
     end
  end
  % highlight the longest line segment
  plot(xy_long(:,1),xy_long(:,2),'LineWidth',2,'Color','red');
  

  

  
• Find Corners of pool table for perspective warp with OpenCV

  I have an image of a pool table with slight perspective distortion:

  

  I am trying to un-warp the image (such that the corners of the pool table correspond to the corners of my output image) and then detect the pool balls on the output image. To unwarp the table, I intend to use cv2.PerspectiveTransform() to obtain the transformation matrix that maps the corners of the pool table to the corners of my output image. However, I do not have the locations of the corners of my table; I want to find the corners programmatically.

  So far, I have applied a mask (that filters out everything but the pool table). After applying the mask, I've applied a Canny edge detector to find the edges of the pool table only:

  

  My idea was to use the Hough line transform algorithm to find the lines corresponding to the edges of the pool table (to find the corners of the pool table programmatically), but the Hough line transform algorithm seems to have a hard time detecting the edges well. How can I find the corners of the pool table from here?