I am a newbie in OpenCV using Python. I am currently working with a project related opencv using python language. I have a video data set named "VideoDataSet/dynamicBackground/canoe/input" that stores the sequence of image frames and I would like to convert the sequence of frames from the file path to a video. However, I am getting an error when I execute the program. I have tried various codecs but it still gives me the same errors, can any of you please shed some light on what might be wrong? Thank you.
This is my sample code:
import cv2
import numpy as np
import os
import glob as gb
filename = "VideoDataSet/dynamicBackground/canoe/input"
img_path = gb.glob(filename)
videoWriter = cv2.VideoWriter('test.avi', cv2.VideoWriter_fourcc(*'MJPG'),
25, (640,480))
for path in img_path:
img = cv2.imread(path)
img = cv2.resize(img,(640,480))
videoWriter.write(img)
print ("you are success create.")
This is the error:
Error prompt out:cv2.error: OpenCV(3.4.1) D:\Build\OpenCV\opencv-3.4.1\modules\imgproc\src\resize.cpp:4044: error: (-215) ssize.width > 0 && ssize.height > 0 in function cv::resize
(Note: the problem occur with the img = cv2.resize(img,(640,480)))
It is returning this error because you are trying to re-size the directory entry! You need to put:
filename = "VideoDataSet/dynamicBackground/canoe/input/*"
So that it will match all the files in the folder when you glob it. The error actually suggested that the source image had either zero width or zero height. Putting:
print( img_path )
In after your glob attempt showed that it was only returning the directory entry itself.
You subsequently discovered that although it was now generating a file, it was corrupted. This is because you are incorrectly specifying the codec. Replace your fourcc parameter with this:
cv2.VideoWriter_fourcc('M','J','P','G')
you can try this:
img_path = gb.glob(filename)
videoWriter = cv2.VideoWriter('frame2video.avi', cv2.VideoWriter_fourcc(*'MJPG'), 25, (640,480))
for path in img_path:
img = cv2.imread(path)
img = cv2.resize(img,(640,480))
videoWriter.write(img)
Related
I would like to import a PDF file and find the most common words.
import PyPDF2
# Open the PDF file and read the text
pdf_file = open("nita20.pdf", "rb")
pdf_reader = PyPDF2.PdfReader(pdf_file)
text = ""
for page in range(pdf_reader.pages):
text += pdf_reader.getPage(page).extractText()
I get this error:
TypeError: '_VirtualList' object cannot be interpreted as an integer
How to resolve this issue? So I can extract every word from the PDF file, thanks.
I got some deprecation warnings on your code, but this works (tested on Python 3.11, PyPDF2 version: 3.0.1)
import PyPDF2
# Open the PDF file and read the text
pdf_file = open("..\test.pdf", "rb")
pdf_reader = PyPDF2.PdfReader(pdf_file)
text = ""
i=0
print(len(pdf_reader.pages))
for page in range(len(pdf_reader.pages)):
text += pdf_reader.pages[i].extract_text()
i=i+1
print(text)
I'm trying to extract text from a pdf file in Russian, and use this text as data for tokenisation, lemmatisation etc. with NLTK on Jupyter Notebook. I'm using PyPDF2, but I keep running into problems.
I am creating a function and passing to it the pdf as the input:
from PyPDF2 import PdfFileReader
def getTextPDF(pdfFileName):
pdf_file = open(pdfFileName, "rb")
read_pdf = PdfFileReader(pdf_file)
text = []
for i in range(0, read_pdf.getNumPages()):
text.append(read_pdf.getPage(i).extractText())
return "\n".join(text)
Then I call the function:
pdfFile = "sample_russian.pdf"
print("PDF: \n", myreader_pdf.getTextPDF(pdfFile))
But I get a long pink list of the same error warning:
PdfReadWarning: Superfluous whitespace found in object header b'1' b'0' [pdf.py:.....]
Any ideas would be very helpful! Thanks in advance!
I have books in pdf and I want to do NLP tasks such as preprocessing, tf-idf calculation, word2vec, etc on those books. So I converted them into .txt files and was trying to get tf-idf scores. Previously I performed tf-idf on a CSV file, so I made some changes in that code and tried to use it for .txt file. But I am unsuccessful in my attempt.
Below is my code:
import pandas as pd
import numpy as np
from itertools import islice
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
data = open('jungle book.txt', 'r+')
# print(data.read())
cvec = CountVectorizer(stop_words='english', min_df=1, max_df=.5, ngram_range=(1,2))
cvec.fit(data)
list(islice(cvec.vocabulary_.items(), 20))
len(cvec.vocabulary_)
cvec_count = cvec.transform(data)
print('Sparse Matrix Shape : ', cvec_count.shape)
print('Non Zero Count : ', cvec_count.nnz)
print('sparsity: %.2f%%' % (100 * cvec_count.nnz / (cvec_count.shape[0] * cvec_count.shape[1])))
occ = np.asarray(cvec_count.sum(axis=0)).ravel().tolist()
count_df = pd.DataFrame({'term': cvec.get_feature_names(), 'occurrences' : occ})
term_freq = count_df.sort_values(by='occurrences', ascending=False).head(20)
print(term_freq)
transformer = TfidfTransformer()
transformed_weights = transformer.fit_transform(cvec_count)
weights = np.asarray(transformed_weights.mean(axis=0)).ravel().tolist()
weight_df = pd.DataFrame({'term' : cvec.get_feature_names(), 'weight' : weights})
tf_idf = weight_df.sort_values(by='weight', ascending=False).head(20)
print(tf_idf)
This code is working until print ('Non Zero Count :', cvec_count.shape) and printing:
Sparse Matrix Shape : (0, 7132)
Non Zero Count : 0
Then it is giving error:
ZeroDivisionError: division by zero
Even if I run this code with ignoring ZeroDivisionError, still it is wrong as it is not counting any frequencies.
I have no idea how to work around .txt file. What is the proper way to work on .txt file for NLP tasks?
Thanks in advance!
You are getting the error because data variable is empty or wrong type. Just opening the text file is not enough. You have to read the contents into a string variable and then do the preprocessing on that variable. Try replacing
data = open('jungle book.txt', 'r+')
# print(data.read())
with
with open('jungle book.txt', 'r') as file:
data = file.read()
I'm trying to convert all type of images in a folder to text using python tesseract. Below is the that I'm using, with this only .png files are being converted to .txt, and other types are not being converted to text.
import os
import pytesseract
import cv2
import re
import glob
import concurrent.futures
import time
def ocr(img_path):
out_dir = "Output//"
img = cv2.imread(img_path)
text = pytesseract.image_to_string(img,lang='eng',config='--psm 6')
out_file = re.sub(".png",".txt",img_path.split("\\")[-1])
out_path = out_dir + out_file
fd = open(out_path,"w")
fd.write("%s" %text)
return out_file
os.environ['OMP_THREAD_LIMIT'] = '1'
def main():
path = input("Enter the path : ")
if os.path.isdir(path) == 1:
out_dir = "ocr_results//"
if not os.path.exists(out_dir):
os.makedirs(out_dir)
with concurrent.futures.ProcessPoolExecutor(max_workers=4) as executor:
image_list = glob.glob(path+"\\*.*")
for img_path,out_file in zip(image_list,executor.map(ocr,image_list)):
print(img_path.split("\\")[-1],',',out_file,', processed')
if __name__ == '__main__':
start = time.time()
main()
end = time.time()
print(end-start)
How to convert all type of image files to text. Please help me with the above code.
There is a bug in the ocr function.
First of all, the following does convert all type of image files to text.
text = pytesseract.image_to_string(img,lang='eng',config='--psm 6'))
However, what the next chunk of code does are
Select those file with .png extension using a regex
Create a new path with the same filename and a a .txt extension
Write the OCR output to the newly create text file.
out_file = re.sub(".png",".txt",img_path.split("\\")[-1])
out_path = out_dir + out_file
fd = open(out_path,"w")
fd.write("%s" %text)
In other words, all types of images files are converted but not all are written back correctly. The regex matching logic only replace .png with .txt and assign to out_path. When there is no .png (other image types), the variable gets the same value as the original filename (e.g. sampe.jpg). The next lines of code open the original image and overwrite with the OCR result.
One way to fix is by adding all the image formats you want to cover into the regex.
For example,
out_file = re.sub(".png|.jpg|.bmp|.tiff",".txt",img_path.split("\\")[-1])
I want to know if it is possible to import data of attitude and position (roll/pitch/yaw & xyz) from a comma separated file to Blender?
I recorded data from a little RC car and I want to represent its movement in a 3D world.
I have timestamps too, so if there's a way to animated the movement of the object it'll be superb!!
Any help will be greatly appreciated!!
Best Regards.
A slight modifcation, making use of the csv module
import bpy
import csv
position_vectors = []
filepath = "C:\\Work\\position.log"
csvfile = open(filepath, 'r', newline='')
ofile = csv.reader(csvfile, delimiter=',')
for row in ofile:
position_vectors.append(tuple([float(i) for i in row]))
csvfile.close()
This will get your points into Blender. Note the delimiter parameter in csv.reader, change that accordingly. With a real example file of your RC car we could provide a more complete solution.
For blender v2.62:
If you have a file "positions.log" looking like:
-8.691985196313894e-002; 4.119284642631801e-001; -5.832147659661263e-001
1.037146774956164e+000; 8.137243553005405e-002; -5.703274929662892e-001
-3.602584527944123e-001; 8.378614512537046e-001; 2.615265921163826e-001
6.266465707681335e-001; -1.128416901202341e+000; -1.664644365541639e+000
3.327523280880091e-001; 4.488553740582839e-001; -2.449449085462368e+000
-7.311567199869298e-001; -1.860587923723032e+000; -1.297179602213110e+000
-7.453603745688361e-003; 4.770473577895327e-001; -2.319515785100494e+000
1.935170866863264e-001; -2.010280476717868e+000; 3.748000986190077e-001
5.201529166915653e-001; 3.952972788761738e-001; 1.658581747430548e+000
4.719198263774027e-001; 1.526020825619557e+000; 3.187088567866725e-002
you can read it with this python script in blender (watch out for the indentation!)
import bpy
from mathutils import *
from math import *
from bpy.props import *
import os
import time
# Init
position_vector = []
# Open file
file = open("C:\\Work\\position.log", "r")
# Loop over line in file
for line in file:
# Split line at ";"
splittet_line = line.split(";")
# Append new postion
position_vector.append(
Vector((float(splittet_line[0]),
float(splittet_line[1]),
float(splittet_line[2]))))
# Close file
file.close()
# Get first selected object
selected_object = bpy.context.selected_objects[0]
# Get first selected object
for position in position_vector:
selected_object.location = position
This reads the file and updates the position of the first selected object accordingly. Way forward: What you have to find out is how to set the keyframes for the animation...
Consider this python snippet to add to the solutions above
obj = bpy.context.object
temporalScale=bpy.context.scene.render.fps
for lrt in locRotArray:
obj.location = (lrt[0], lrt[1], lrt[2])
# radians, and do you want XYZ, or ZYX?
obj.rotation_euler = (lrt[3], lrt[4], lrt[5])
time = lrt[6]*temporalScale
obj.keyframe_insert(data_path="location", frame=time)
obj.keyframe_insert(data_path="rotation_euler", frame=time)
I haven't tested it, but it will probably work, and gets you started.
With a spice2xyzv file as input file. The script writed by "Mutant Bob" seems to work.
But the xyz velocity data are km/s not euler angles, I think, and the import does not work for the angles.
# Records are <jd> <x> <y> <z> <vel x> <vel y> <vel z>
# Time is a TDB Julian date
# Position in km
# Velocity in km/sec
2456921.49775 213928288.518 -446198013.001 -55595492.9135 6.9011736 15.130842 0.54325805
Is there a solution to get them in Blender? Should I convert velocity angle to euler, is that possible in fact?
I use this script :
import bpy
from mathutils import *
from math import *
from bpy.props import *
import os
import time
# Init
position_vector = []
# Open file
file = open("D:\\spice2xyzv\\export.xyzv", "r")
obj = bpy.context.object
temporalScale=bpy.context.scene.render.fps
for line in file:
# Split line at ";"
print("line = %s" % line)
line = line.replace("\n","")
locRotArray = line.split(" ")
print("locRotArray = %s" % locRotArray )
#for lrt in locRotArray:
print(locRotArray[1])
obj.location = (float(locRotArray[1]), float(locRotArray[2]), float(locRotArray[3]))
# radians, and do you want XYZ, or ZYX?
obj.rotation_euler = (float(locRotArray[4]), float(locRotArray[5]), float(locRotArray[5]))
time = float(locRotArray[0])*temporalScale
print("time = %s" % time)
obj.keyframe_insert(data_path="location", frame=time)
obj.keyframe_insert(data_path="rotation_euler", frame=time)