bnsreenu / python_for_image_processing_apeer Goto Github PK
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I'm implementing a UNet neural network but I'm having some issues while importing libraries. I found a solution for a couple of them, but I still have a problem with these two imports:
`from tensorflow.keras.optimizers import Adam
#Import "tensorflow.keras.optimizers" could not be resolved(reportMissingImports)
from tensorflow.keras.preprocessing.image import ImageDataGenerator
#Import "tensorflow.keras.preprocessing.image" could not be resolved(reportMissingImports)
`
Any idea?i've tryed some changes but it's still not working
i try with another dataset, it always crashed in:
#XGBOOST
import xgboost as xgb
model = xgb.XGBClassifier(tree_method='gpu_hist', gpu_id=0)
model.fit(X_for_training, y_train) #For sklearn no one hot encoding <---- (this part)
i already try with local PC too, there's bug:
AttributeError: 'bool' object has no atribute 'all'
could someone solve my problem please. many thanks
Hi,
Thank you for sharing this code.
I have two (reference and tested) images of different sizes (H*W). The PSNR and RMSE in the code did not work with different shapes.
Is there a way to assess the two images with different shapes?
Thank you in advanced
Sir, inspired by your tutorial and other references I tried with HOCR output, but 3 things is pulling me back from final output.
`# Python program to extract text from all the images in a folder
from PIL import Image
import pytesseract as pt
import os
pt.pytesseract.tesseract_cmd = r'C:\Users\admin\AppData\Local\Programs\Tesseract-OCR\tesseract.exe'
def main():
# path for the folder for getting the raw images
path ="D:\input"
# path for the folder for getting the output
tempPath ="D:\\output\"
# iterating the images inside the folder
for imageName in os.listdir(path):
inputPath = os.path.join(path, imageName)
img = Image.open(inputPath)
#config =('--oem 3--psm 6')
# applying ocr using pytesseract for python
#custom_config = r'--oem 3 --psm 6'
#text=pt.image_to_string(img, config=custom_config)
text = pt.image_to_pdf_or_hocr(img, extension = 'hocr', config = (r'--oem 3 --psm 6'), lang ="eng")
# for removing the .jpg from the imagePath
#imagePath = imagePath[0:-4]
fullTempPath = os.path.join(tempPath, 'time_'+imageName+".hocr")
print(text)
# saving the text for every image in a separate .txt file
file1 = open(fullTempPath, "wb")
file1.write(text)
file1.close()
if name == 'main':
main()
`
data/k-means.xlsx missing in tutorial71
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