finding barcode
This commit is contained in:
shaaqu
parent
ea4f66531d
commit
bb070b8085
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@ -19,12 +19,11 @@
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<change afterPath="$PROJECT_DIR$/coder/test5.png" afterDir="false" />
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<list default="true" id="828778c9-9d97-422f-a727-18ddbd059b85" name="Default Changelist" comment="zwiekszenie dokladnosci">
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<change afterPath="$PROJECT_DIR$/coder/barcode.jpg" afterDir="false" />
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<change beforePath="$PROJECT_DIR$/coder/test3.png" beforeDir="false" afterPath="$PROJECT_DIR$/coder/test3.png" afterDir="false" />
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@ -82,7 +81,7 @@
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<recent name="C:\Users\Pawel Lukaszewicz\PycharmProjects\AL-2020\coder" />
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@ -105,28 +104,6 @@
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@ -190,6 +167,25 @@
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<option name="INPUT_FILE" value="" />
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<option name="PARENT_ENVS" value="true" />
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<option name="SDK_HOME" value="" />
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<option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/coder" />
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<option name="IS_MODULE_SDK" value="true" />
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<option name="ADD_CONTENT_ROOTS" value="true" />
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<option name="ADD_SOURCE_ROOTS" value="true" />
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<EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
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<option name="SCRIPT_NAME" value="$PROJECT_DIR$/coder/rocognizer.py" />
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<option name="EMULATE_TERMINAL" value="false" />
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<option name="MODULE_MODE" value="false" />
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@ -210,19 +206,19 @@
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<method v="2" />
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@ -248,7 +244,7 @@
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<created>1589815443652</created>
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@ -299,7 +295,14 @@
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<option name="project" value="LOCAL" />
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<updated>1589955873104</updated>
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@ -326,7 +329,8 @@
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<MESSAGE value="img to 1d array" />
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<MESSAGE value="fun created" />
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<MESSAGE value="recognizing but training must be improved" />
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<option name="LAST_COMMIT_MESSAGE" value="recognizing but training must be improved" />
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<MESSAGE value="zwiekszenie dokladnosci" />
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Binary file not shown.
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After Width: | Height: | Size: 42 KiB |
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@ -32,7 +32,7 @@ print(accuracy_score(y_test, predictions))
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# image
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img = cv2.cvtColor(cv2.imread('test3.png'), cv2.COLOR_BGR2GRAY)
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img = cv2.GaussianBlur(img, (5, 5), 0) # poprawia jakosc
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img = cv2.blur(img, (9, 9)) # poprawia jakosc
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img = cv2.resize(img, (8, 8), interpolation=cv2.INTER_AREA)
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print(type(img))
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@ -47,7 +47,7 @@ rows, cols = img.shape
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for i in range(rows):
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for j in range(cols):
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k = img[i, j]
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if k == 255:
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if k > 225:
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k = 0 # brak czarnego
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else:
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k = 1
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@ -1,13 +1,37 @@
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import matplotlib.pyplot as plt
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import numpy as np
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from numpy import asarray
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from sklearn import datasets
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from sklearn.neural_network import MLPClassifier
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from sklearn.metrics import accuracy_score
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from PIL import Image
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import pygame
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import functions
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import sys
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import time
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import argparse
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import imutils
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import cv2
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import matplotlib.pyplot as plt
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img = cv2.cvtColor(cv2.imread('barcode.jpg'), cv2.COLOR_BGR2GRAY)
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ddepth = cv2.cv.CV_32F if imutils.is_cv2() else cv2.CV_32F
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X = cv2.Sobel(img, ddepth=ddepth, dx=1, dy=0, ksize=-1)
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Y = cv2.Sobel(img, ddepth=ddepth, dx=0, dy=1, ksize=-1)
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gradient = cv2.subtract(X, Y)
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gradient = cv2.convertScaleAbs(gradient)
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blurred = cv2.blur(gradient, (9, 9))
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(_, thresh) = cv2.threshold(blurred, 225, 255, cv2.THRESH_BINARY)
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kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (21, 7))
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closed = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
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closed = cv2.erode(closed, None, iterations=4)
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closed = cv2.dilate(closed, None, iterations=4)
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cnts = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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cnts = imutils.grab_contours(cnts)
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c = sorted(cnts, key=cv2.contourArea, reverse=True)[0]
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rect = cv2.minAreaRect(c)
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box = cv2.cv.BoxPoints(rect) if imutils.is_cv2() else cv2.boxPoints(rect)
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box = np.int0(box)
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cv2.drawContours(img, [box], -1, (0, 255, 0), 3)
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cv2.imshow("Image", img)
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cv2.waitKey(0)
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plt.imshow(closed ,cmap='binary')
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plt.show()
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