I'm trying to read and get the location of the white text on the black background using pytesseract, but am not having any success. Here is an example of an image that I'm dealing with.
Here is the code:
import cv2
import pytesseract
from pytesseract import Output
img = cv2.imread("ocr_example.png")
img = cv2.bitwise_not(img)
_, binary = cv2.threshold(img, 150, 255, cv2.THRESH_BINARY)
custom_config = r'--oem 3 --psm 6'
d = pytesseract.image_to_data(binary, output_type=Output.DICT, config=custom_config)
print(d["text"])
Here is the output of the text found:
['', '', '', '', 'Home', 'Address', '', 'Use', 'Current', 'Location', '', '>', '', 'Unable', 'to', 'find', 'location']
If I save the white text on black background to its own file and scan, the text is found without a problem. But I need to get the location of the text on the image as a whole.
I've tried using many of the Preprocessing suggestions on sites like https://nanonets.com/blog/ocr-with-tesseract/, but nothing seems to work. I don't mind doing a second search that finds only the missing text.
The problem is you set page-segmentation-mode to recognize single uniform block of text from the given image. (6)
Change to recognize single column of text of variable sizes. (4)
Source pytesseract-ocr-multiple-config-options
All you need to change --psm 6 to --psm 4.
Now read
Home Address
Enter address here
Use Current Location
Unable to find location
DISMISS SAVE
Code:
import cv2
import pytesseract
img = cv2.imread("hm-adrs.png")
img = cv2.bitwise_not(img)
_, binary = cv2.threshold(img, 150, 255, cv2.THRESH_BINARY)
txt = pytesseract.image_to_string(binary, config="--oem 3 --psm 4")
print(txt)
# gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# threshold_img = cv2.threshold(binary, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
worked better. Passing the threshold_img to the pytesseract.image_to_data with custom_config = r'--oem 3 --psm 4'
Related
I'm using the following code to check the coherence value. The problem is code below works well when I change the coherence type into "u_mass", but if I want to compute "c_v", an Index error occure.
Previous text process:
# Remove Stopwords, Form Bigrams, Trigrams and Lemmatization
def process_words(texts, stop_words=stop_words, allowed_postags=['NOUN', 'ADJ', 'VERB', 'ADV']):
texts = [[word for word in simple_preprocess(str(doc)) if word not in stop_words] for doc in texts]
texts = [bigram_mod[doc] for doc in texts]
texts = [trigram_mod[bigram_mod[doc]] for doc in texts]
texts_out = []
nlp = spacy.load("en_core_web_sm", disable=['parser', 'ner'])
for sent in texts:
doc = nlp(" ".join(sent))
texts_out.append([token.lemma_ for token in doc if token.pos_ in allowed_postags])
# remove stopwords once more after lemmatization
texts_out = [[word for word in simple_preprocess(str(doc)) if word not in stop_words] for doc in texts_out]
## Remove numbers, but not words that contain numbers.
texts_out = [[word for word in simple_preprocess(str(doc)) if not word.isdigit()] for doc in texts_out]
## Remove words that are only one character.
texts_out = [[word for word in simple_preprocess(str(doc)) if len(word) > 3] for doc in texts_out]
return texts_out
data_ready = process_words(data_words)
# Create Dictionary
id2word = corpora.Dictionary(data_ready)
#dictionary.filter_extremes(no_below=10, no_above=0.2) #filter out tokens
# Create Corpus: Term Document Frequency
corpus = [id2word.doc2bow(text) for text in data_ready]
# View:the produced corpus shown above is a mapping of (word_id, word_frequency).
print(corpus[:1])
print('Number of unique tokens: %d' % len(id2word))
print('Number of documents: %d' % len(corpus))
The output is :
[[(0, 1), (1, 1), (2, 1), (3, 1)]]
Number of unique tokens: 6558
Number of documents: 23141
Now I set a base model:
## set a base model
num_topics = 5
chunksize = 100
passes = 10
iterations = 100
eval_every = 1
lda_model = LdaModel(corpus=corpus,id2word=id2word, chunksize=chunksize, \
alpha='auto', eta='auto', \
iterations=iterations, num_topics=num_topics, \
passes=passes, eval_every=eval_every)
The last step is where the problem occurs:
# Compute Coherence Score
coherence_model_lda = CoherenceModel(model=lda_model, texts=data_ready, dictionary=id2word, coherence="c_v")
coherence_lda = coherence_model_lda.get_coherence()
print('\nCoherence Score: ', coherence_lda)
Here is the error:
IndexError: index 0 is out of bounds for axis 0 with size 0
If I change coherence into 'u_mass', however, the code ablove can compute successfully. I don't understand why and how to fix it?
!pip install gensim==4.1.0
It seems that downgrade solves everything.
Just in case anyone else runs into the same issue.
Apparently the error described here persist in gensim 4.2.0. Downgrading to 4.1.0 worked well for me.
I am creating a python script that can read scanned, and tabular .pdfs and extract some important data and insert it into a JSON to later be implemented into a SQL database (I will also be developing the DB as a project for learning MongoDB).
Basically, my issue is I have never worked with any JSON files before but that was the format I was recommended to output to. The scraping script works, the pre-processing could be a lot cleaner, but for now it works. The issue I run into is the keys, and values are in the same list, and some of the values because they had a decimal point are two different list items. Not really sure where to even start.
I don't really know where to start, I suppose since I know what the indexes of the list are I can easily assign keys and values, but then it may not be applicable to any .pdf, that is the script cannot be coded explicitly.
import PyPDF2 as pdf2
import textract
with "TestSpec.pdf" as filename:
pdfFileObj = open(filename, 'rb')
pdfReader = pdf2.pdfFileReader(pdfFileObj)
num_pages = pdfReader.numpages
count = 0
text = ""
while count < num_pages:
pageObj = pdfReader.getPage(0)
count += 1
text += pageObj.extractText()
if text != "":
text = text
else:
text = textract.process(filename, method="tesseract", language="eng")
def cleanText(x):
'''
This function takes the byte data extracted from scanned PDFs, and cleans it of all
unnessary data.
Requires re
'''
stringedText = str(x)
cleanText = stringedText.replace('\n','')
splitText = re.split(r'\W+', cleanText)
caseingText = [word.lower() for word in splitText]
cleanOne = [word for word in caseingText if word != 'n']
dexStop = cleanOne.index("od260")
dexStart = cleanOne.index("sheet")
clean = cleanOne[dexStart + 1:dexStop]
return clean
cleanText = cleanText(text)
This is the current output
['n21', 'feb', '2019', 'nsequence', 'lacz', 'rp', 'n5', 'gat', 'ctc', 'tac', 'cat', 'ggc', 'gca', 'cat', 'ttc', 'ccc', 'gaa', 'aag', 'tgc', '3', 'norder', 'no', '15775199', 'nref', 'no', '207335463', 'n25', 'nmole', 'dna', 'oligo', '36', 'bases', 'nproperties', 'amount', 'of', 'oligo', 'shipped', 'to', 'ntm', '50mm', 'nacl', '66', '8', 'xc2', 'xb0c', '11', '0', '32', '6', 'david', 'cook', 'ngc', 'content', '52', '8', 'd260', 'mmoles', 'kansas', 'state', 'university', 'biotechno', 'nmolecular', 'weight', '10', '965', '1', 'nnmoles']
and we want the output as a JSON setup like
{"Date | 21feb2019", "Sequence ID: | lacz-rp", "Sequence 5'-3' | gat..."}
and so on. Just not sure how to do that.
here is a screenshot of the data from my sample pdf
So, i have figured out some of this. I am still having issues with grabbing the last 3rd of the data i need without explicitly programming it in. but here is what i have so far. Once i have everything working then i will worry about optimizing it and condensing.
# for PDF reading
import PyPDF2 as pdf2
import textract
# for data preprocessing
import re
from dateutil.parser import parse
# For generating the JSON file array
import json
# This finds and opens the pdf file, reads the data, and extracts the data.
filename = "*.pdf"
pdfFileObj = open(filename, 'rb')
pdfReader = pdf2.PdfFileReader(pdfFileObj)
text = ""
pageObj = pdfReader.getPage(0)
text += pageObj.extractText()
# checks if extracted data is in string form or picture, if picture textract reads data.
# it then closes the pdf file
if text != "":
text = text
else:
text = textract.process(filename, method="tesseract", language="eng")
pdfFileObj.close()
# Converts text to string from byte data for preprocessing
stringedText = str(text)
# Removed escaped lines and replaced them with actual new lines.
formattedText = stringedText.replace('\\n', '\n').lower()
# Slices the long string into a workable piece (only contains useful data)
slice1 = formattedText[(formattedText.index("sheet") + 10): (formattedText.index("secondary") - 2)]
clean = re.sub('\n', " ", slice1)
clean2 = re.sub(' +', ' ', clean)
# Creating the PrimerData dictionary
with open("PrimerData.json",'w') as file:
primerDataSlice = clean[clean.index("molecular"): -1]
primerData = re.split(": |\n", primerDataSlice)
primerKeys = primerData[0::2]
primerValues = primerData[1::2]
primerDict = {"Primer Data": dict(zip(primerKeys,primerValues))}
# Generatring the JSON array "Primer Data"
primerJSON = json.dumps(primerDict, ensure_ascii=False)
file.write(primerJSON)
# Grabbing the date (this has just the date, so json will have to add date.)
date = re.findall('(\d{2}[\/\- ](\d{2}|january|jan|february|feb|march|mar|april|apr|may|may|june|jun|july|jul|august|aug|september|sep|october|oct|november|nov|december|dec)[\/\- ]\d{2,4})', clean2)
Without input data it is difficult to give you working code. A minimal working example with input would help. As for JSON handling, python dictionaries can dump to json easily. See examples here.
https://docs.python-guide.org/scenarios/json/
Get a json string from a dictionary and write to a file. Figure out how to parse the text into a dictionary.
import json
d = {"Date" : "21feb2019", "Sequence ID" : "lacz-rp", "Sequence 5'-3'" : "gat"}
json_data = json.dumps(d)
print(json_data)
# Write that data to a file
So, I did figure this out, the problem was really just that because of the way my pre-processing was pulling all the data into a single list wasn't really that great of an idea considering that the keys for the dictionary never changed.
Here is the semi-finished result for making the Dictionary and JSON file.
# Collect the sequence name
name = clean2[clean2.index("Sequence") + 11: clean2.index("Sequence") + 19]
# Collecting Shipment info
ordered = input("Who placed this order? ")
received = input("Who is receiving this order? ")
dateOrder = re.findall(
r"(\d{2}[/\- ](\d{2}|January|Jan|February|Feb|March|Mar|April|Apr|May|June|Jun|July|Jul|August|Aug|September|Sep|October|Oct|November|Nov|December|Dec)[/\- ]\d{2,4})",
clean2)
dateReceived = date.today()
refNo = clean2[clean2.index("ref.No. ") + 8: clean2.index("ref.No.") + 17]
orderNo = clean2[clean2.index("Order No.") +
10: clean2.index("Order No.") + 18]
# Finding and grabbing the sequence data. Storing it and then finding the
# GC content and melting temp or TM
bases = int(clean2[clean2.index("bases") - 3:clean2.index("bases") - 1])
seqList = [line for line in clean2 if re.match(r'^[AGCT]+$', line)]
sequence = "".join(i for i in seqList[:bases])
def gc_content(x):
count = 0
for i in x:
if i == 'G' or i == 'C':
count += 1
else:
count = count
return round((count / bases) * 100, 1)
gc = gc_content(sequence)
tm = mt.Tm_GC(sequence, Na=50)
moleWeight = round(mw(Seq(sequence, generic_dna)), 2)
dilWeight = float(clean2[clean2.index("ug/OD260:") +
10: clean2.index("ug/OD260:") + 14])
dilution = dilWeight * 10
primerDict = {"Primer Data": {
"Sequence": sequence,
"Bases": bases,
"TM (50mM NaCl)": tm,
"% GC content": gc,
"Molecular weight": moleWeight,
"ug/0D260": dilWeight,
"Dilution volume (uL)": dilution
},
"Shipment Info": {
"Ref. No.": refNo,
"Order No.": orderNo,
"Ordered by": ordered,
"Date of Order": dateOrder,
"Received By": received,
"Date Received": str(dateReceived.strftime("%d-%b-%Y"))
}}
# Generating the JSON array "Primer Data"
with open("".join(name) + ".json", 'w') as file:
primerJSON = json.dumps(primerDict, ensure_ascii=False)
file.write(primerJSON)
I've been given a load of JSON files which I'm trying to load into python 3.5
I've already had to do some clean up work, removing double backslashes and extra quotations, however I've run into an issue I don't know how to solve.
I'm running the following code:
with open(filepath,'r') as json_file:
reader = json_file.readlines()
for row in reader:
row = row.replace('\\', '')
row = row.replace('"{', '{')
row = row.replace('}"', '}')
response = json.loads(row)
for i in response:
responselist.append(i['ActionName'])
However it's throwing up the error:
JSONDecodeError: Expecting ',' delimiter: line 1 column 388833 (char 388832)
The part of the JSON that's causing the issue is the status text entry below:
"StatusId":8,
"StatusIdString":"UnknownServiceError",
"StatusText":"u003cCompany docTypeu003d"Mobile.Tile" statusIdu003d"421" statusTextu003d"Start time of 11/30/2015 12:15:00 PM is more than 5 minutes in the past relative to the current time of 12/1/2015 12:27:01 AM." copyrightu003d"Copyright Company Inc." versionNumberu003d"7.3" createdDateu003d"2015-12-01T00:27:01Z" responseIdu003d"e74710c0-dc7c-42db-b608-bf905d95d153" /u003e",
"ActionName":"GetTrafficTile"
I added the line breaks to illustrate my point, it looks like python is unhappy that the string contains double quotes.
I have a feeling this may be to do with my replacing '\ \' with '' messing with the unicode characters in the string. Is there any way to repair these nested strings? I don't mind if the StatusText field is deleted completely, all I'm after is a list of the ActionName fields.
EDIT:
I've hosted an example file here:
https://www.dropbox.com/s/1oanrneg3aqandz/2015-12-01T00%253A00%253A42.527Z_2015-12-01T00%253A01%253A17.478Z?dl=0
This is exactly as I received, before I've replaced the extra backslashes and quotations
Here is a pared down version of the sample with one bad entry
["{\"apiServerType\":0,\"RequestId\":\"52a65260-1637-4653-a496-7555a2386340\",\"StatusId\":0,\"StatusIdString\":\"Ok\",\"StatusText\":null,\"ActionName\":\"GetCameraImage\",\"Url\":\"http://mosi-prod.cloudapp.net/api/v1/GetCameraImage?AuthToken=vo*AB57XLptsKXf0AzKjf1MOgQ1hZ4BKipKgYl3uGew%7C&CameraId=13782\",\"Lat\":0.0,\"Lon\":0.0,\"iVendorId\":12561,\"iConsumerId\":2986897,\"iSliverId\":51846,\"UserId\":\"2986897\",\"HardwareId\":null,\"AuthToken\":\"vo*AB57XLptsKXf0AzKjf1MOgQ1hZ4BKipKgYl3uGew|\",\"RequestTime\":\"2015-12-01T00:00:42.5278699Z\",\"ResponseTime\":\"2015-12-01T00:01:02.5926127Z\",\"AppId\":null,\"HttpMethod\":\"GET\",\"RequestHeaders\":\"{\\\"Connection\\\":[\\\"keep-alive\\\"],\\\"Via\\\":[\\\"HTTP/1.1 nycnz01msp1ts10.wnsnet.attws.com\\\"],\\\"Accept\\\":[\\\"application/json\\\"],\\\"Accept-Encoding\\\":[\\\"gzip\\\",\\\"deflate\\\"],\\\"Accept-Language\\\":[\\\"en-us\\\"],\\\"Host\\\":[\\\"mosi-prod.cloudapp.net\\\"],\\\"User-Agent\\\":[\\\"Traffic/5.4.0\\\",\\\"CFNetwork/758.1.6\\\",\\\"Darwin/15.0.0\\\"]}\",\"RequestContentHeaders\":\"{}\",\"RequestContentBody\":\"\",\"ResponseBody\":null,\"ResponseContentHeaders\":\"{\\\"Content-Type\\\":[\\\"image/jpeg\\\"]}\",\"ResponseHeaders\":\"{}\",\"MiniProfilerJson\":null}"]
The problem is a little different than you think. Whatever program built these files used data that was already json-encoded and ended up double and even triple encoding some of the information. I peeled it apart in a shell session and got usable python data. You can (1) go dope-slap whoever wrote the program that built this steaming pile of... um... goodness? and (2) manually scan through and decode inner json strings.
I decoded the data and it was a list of strings, but those strings looked suspiciously like json
>>> data = json.load(open('test.json'))
>>> type(data)
<class 'list'>
>>> d0 = data[0]
>>> type(d0)
<class 'str'>
>>> d0[:70]
'{"apiServerType":0,"RequestId":"52a65260-1637-4653-a496-7555a2386340",'
Sure enough, I can decode it
>>> d0_1 = json.loads(d0)
>>> type(d0_1)
<class 'dict'>
>>> d0_1
{'ResponseBody': None, 'StatusText': None, 'AppId': None, 'ResponseTime': '2015-12-01T00:01:02.5926127Z', 'HardwareId': None, 'RequestTime': '2015-12-01T00:00:42.5278699Z', 'StatusId': 0, 'Lon': 0.0, 'Url': 'http://mosi-prod.cloudapp.net/api/v1/GetCameraImage?AuthToken=vo*AB57XLptsKXf0AzKjf1MOgQ1hZ4BKipKgYl3uGew%7C&CameraId=13782', 'RequestContentBody': '', 'RequestId': '52a65260-1637-4653-a496-7555a2386340', 'MiniProfilerJson': None, 'RequestContentHeaders': '{}', 'ActionName': 'GetCameraImage', 'StatusIdString': 'Ok', 'HttpMethod': 'GET', 'iSliverId': 51846, 'ResponseHeaders': '{}', 'ResponseContentHeaders': '{"Content-Type":["image/jpeg"]}', 'apiServerType': 0, 'AuthToken': 'vo*AB57XLptsKXf0AzKjf1MOgQ1hZ4BKipKgYl3uGew|', 'iConsumerId': 2986897, 'RequestHeaders': '{"Connection":["keep-alive"],"Via":["HTTP/1.1 nycnz01msp1ts10.wnsnet.attws.com"],"Accept":["application/json"],"Accept-Encoding":["gzip","deflate"],"Accept-Language":["en-us"],"Host":["mosi-prod.cloudapp.net"],"User-Agent":["Traffic/5.4.0","CFNetwork/758.1.6","Darwin/15.0.0"]}', 'iVendorId': 12561, 'Lat': 0.0, 'UserId': '2986897'}
Picking one of the entries, that looks like more json
>>> hdrs = d0_1['RequestHeaders']
>>> type(hdrs)
<class 'str'>
Yep, it decodes to what I want
>>> hdrs_0 = json.loads(hdrs)
>>> type(hdrs_0)
<class 'dict'>
>>>
>>> hdrs_0["Via"]
['HTTP/1.1 nycnz01msp1ts10.wnsnet.attws.com']
>>>
>>> type(hdrs_0["Via"])
<class 'list'>
Here you are :) :
responselist = []
with open('dataFile.json','r') as json_file:
reader = json_file.readlines()
for row in reader:
strActNm = 'ActionName":"'; lenActNm = len(strActNm)
actionAt = row.find(strActNm)
while actionAt > 0:
nxtQuotAt = row.find('"',actionAt+lenActNm+2)
responselist.append( row[actionAt-1: nxtQuotAt+1] )
actionAt = row.find('ActionName":"', nxtQuotAt)
print(responselist)
which gives:
>python3.6 -u "dataFile.py"
['"ActionName":"GetTrafficTile"']
>Exit code: 0
where dataFile.json is the file with the line you provided and dataFile.py the code provided above.
It's the hard tour, but if the files are in a bad format you have to find a way around and a simple pattern matching works in any case. For more complex cases you will need regex (regular expressions), but in this case a simple .find() is enough to do the job.
The code finds also multiple "actions" in the line (if the line would contain more than one action).
Here the result for the file you provided in your link while using following small modification of the code above:
responselist = []
with open('dataFile1.json','r') as json_file:
reader = json_file.readlines()
for row in reader:
strActNm='\\"ActionName\\":\\"'
# strActNm = 'ActionName":"'
lenActNm = len(strActNm)
actionAt = row.find(strActNm)
while actionAt > 0:
nxtQuotAt = row.find('"',actionAt+lenActNm+2)
responselist.append( row[actionAt: nxtQuotAt+1].replace('\\','') )
actionAt = row.find('ActionName":"', nxtQuotAt)
print(responselist)
gives:
>python3.6 -u "dataFile.py"
['"ActionName":"GetCameraImage"']
>Exit code: 0
where dataFile1.json is the file you provided in the link.
I am taking several comma delimited CSV files and using them to generate an XLS spreadsheet in which the names of the files become separate tabs in the spreadsheet. The code I have produces the results I want except for when opening the spreadsheet I get the following warning: "Some text formatting may have changed in this file because the maximum number of fonts was exceeded. It may help to close other documents and try again." I am pretty sure that the problem arises from the code trying to change the format of cells beyond the 65536 row limit, but I'm not sure how to limit the row changes. I need no more than a few hundred rows across four columns.
import csv, glob, xlwt, sys, os
csvFiles = os.path.join(LogFileFolder, "*")
wb = xlwt.Workbook()
colNames = ['iNFADS_FAC','CAT','Crosswalk_FAC','FAC']
for filename in glob.glob(csvFiles):
(f_path, f_name) = os.path.split(filename)
(f_short_name, f_extension) = os.path.splitext(f_name)
ws = wb.add_sheet(f_short_name)
with open(filename, 'rb') as csvf:
csvReader = csv.reader(csvf)
for rowx, row in enumerate(csvReader):
for colx, value in enumerate(row):
if value in colNames:
ws.write(rowx, colx, value, xlwt.easyxf(
"border: top medium, right medium, bottom double, left medium;
font: bold on; pattern: pattern solid, fore_color pale_blue;
align: vert centre, horiz centre"))
elif value not in colNames:
ws.write(rowx, colx, float(value),
xlwt.easyxf("align: vert centre, horiz centre"))
##This second "xlwt.easyxf(align...)" part is the offending section of the code, if
##I remove just that part then the problem goes away. Is there a way to keep
##it within the 65536 limit here?
else:
pass
wb.set_active_sheet = 1
outXLS = os.path.join(LogFileFolder, "FAC-CAT Code Changes.xls")
wb.save(outXLS)
I wish to thank John Machin at Google Group 'python-excel' for answering my question. Apparently, the solution is to move the easyxf portion to a variable earlier in the script and then just call it whenever needed. So the script should read:
csvFiles = os.path.join(LogFileFolder, "*")
wb = xlwt.Workbook()
headerStyle = xlwt.easyxf("border: top medium, right medium, bottom double," \
"left medium; font: bold on; pattern: pattern solid, fore_color pale_blue;" \
"align: vert centre, horiz centre")
valueStyle = xlwt.easyxf("align: vert centre, horiz centre")
colNames = ['iNFADS_FAC','CAT','Crosswalk_FAC','FAC']
for filename in glob.glob(csvFiles):
(f_path, f_name) = os.path.split(filename)
(f_short_name, f_extension) = os.path.splitext(f_name)
ws = wb.add_sheet(f_short_name)
with open(filename, 'rb') as csvf:
csvReader = csv.reader(csvf)
for rowx, row in enumerate(csvReader):
for colx, value in enumerate(row):
if value in colNames:
ws.col(colx).width = 256 * 15
ws.write(rowx, colx, value, headerStyle)
elif value not in colNames:
ws.write(rowx, colx, float(value), valueStyle)
else:
pass
wb.set_active_sheet = 1
outXLS = os.path.join(LogFileFolder, "FAC-CAT Code Changes.xls")
wb.save(outXLS)
I have a simple captcha,I want to recognize the picture.
the picture is like:
I want to use the tesseract. http://code.google.com/p/tesseract-ocr/
but the tesseract only can use on the clear picture.
so I should preprocess the pic.
the preprocess code is:
im = Image.open('test.png')
# text = image_to_string(im)
enhancer = ImageEnhance.Contrast(im)
im = enhancer.enhance(4)
img = img.convert("RGBA")
width,height = im.size
# pixdata = img.load()
for y in xrange(img.size[1]):
for x in xrange(img.size[0]):
if im.getpixel((x,y)) != (0,0,0):
im.putpixel((x,y),(255,255,255) )
for y in xrange(img.size[1]):
for x in xrange(img.size[0]):
if y<2 or y>(img.size[1]-3):
continue
if im.getpixel((x, y))[0]==255 and im.getpixel((x, y+2))[0]==0 and im.getpixel((x, y-1))[0]==0:
im.putpixel((x, y),(0,0,0))
# else:
# continue
list(im.getdata())
im.show()
after the process,the pic is like:
so I failed. can anyone give me some tips?
I know how to remove the line if the line is a pixel width,but the line here is not consistent.