def templating():
if 'filename' not in request.args:
return 'please provide filename argument e.g \\templating?filename=example.png',400
if 'templateSize' in request.args:
templateSize = request.args['templateSize']
else:
templateSize = 15
template = np.full((templateSize, templateSize), 0, dtype=np.uint8)
template = cv2.circle(template, (int(templateSize / 2), int(templateSize / 2)), 5, 255, cv2.FILLED)
m = Templating(template, 0.50)
filename = request.args['filename']
filepath = app.root_path + '/' + app.config['UPLOAD_FOLDER'] + '/' + secure_filename(filename)
im = ImageManager(filepath)
im.singleLayerFind(m,0)
templateFile = filename.rsplit('.', 1)[0] + '_template.' + filename.rsplit('.', 1)[1]
templateFilepath = filepath.rsplit('.', 1)[0] + '_template.' + filepath.rsplit('.', 1)[1]
im.saveIntermidiary(templateFilepath)
im.outline_mammal()
outlinedFile = filename.rsplit('.', 1)[0] + '_template_outlined.' + filename.rsplit('.', 1)[1]
outlinedFilepath = filepath.rsplit('.', 1)[0] + '_template_outlined.' + filepath.rsplit('.', 1)[1]
im.saveOutlined(outlinedFilepath)
return render_template('result.html', title='results', intermidaryFile=templateFile, outlinedFile=outlinedFile)
def colourBandCombiner():
s: ImageManager = ImageManager('images/image-4.tif')
image = s.combineToSingleLayer([0.2,0.2,0.2,-0.2,-0.2])
image = cv2.normalize(image, None, 0, 255, cv2.NORM_MINMAX, cv2.CV_8U)
fig: plt.Figure = plt.figure()
fig.suptitle('Combined')
ax: Axes3D = fig.add_subplot(111, projection='3d')
x = range(image.shape[0])
y = range(image.shape[1])
print(image.shape)
X, Y = np.meshgrid(x, y)
ax.plot_surface(X.T, Y.T, image)
plt.savefig('images/image-4-combined.png')
s: ImageManager = ImageManager('images/image-4.tif')
image = s.combineToSingleLayer([0.2, 0.2, 0.2, -0.2, -0.2])
image = cv2.normalize(image, None, 0, 255, cv2.NORM_MINMAX, cv2.CV_8U)
row = image[4]
#print(row)
sum = 0
for x in row:
sum = sum + x
backav = sum / len(row)
print('background', backav)
sheep = image[27, 25:39]
#print(sheep)
sum = 0
for x in sheep:
sum = sum + x
sheepav = sum / len(sheep)
print('sheep', sheepav)
print('dif', sheepav - backav)
def large_file_th():
m = Thresholding(threshold_value=220)
s: ImageManager = ImageManager("images/image3.tif")
s.singleLayerFind(m, 3)
s.saveIntermidiary('images/threshold.tif')
s.outline_mammal()
s.saveOutlined('images/outline.tif')
def single_channel_small_tiff_th():
m = Thresholding(threshold_value=120, min_pixels_in_sheep=10)
s: ImageManager = ImageManager("images/image.TIF")
s.singleLayerFind(m, 0)
s.saveIntermidiary('images/result/threshold.tif')
s.outline_mammal(baseImage='original')
s.saveOutlined('images/result/outline.tif')
def single_channel_small_tiff():
template = np.zeros((30, 30), dtype=np.uint8)
template = cv2.circle(template, (15, 15), 10, 255, cv2.FILLED)
m = Templating(template, 0.75)
s: ImageManager = ImageManager("images/image.TIF")
s.singleLayerFind(m, 0)
s.saveIntermidiary('images/result/templating.tif')
s.outline_mammal(baseImage='original')
s.saveOutlined('images/result/outlinetemplating.tif')
def three_channel_file_th():
"""Main algorithm for this attempt using thresholding"""
m = Thresholding(threshold_value=180)
s: ImageManager = ImageManager("images/image2.JPG")
s.singleLayerFind(m, 0)
s.saveIntermidiary('images/result/threshold2.png')
s.outline_mammal(baseImage='original')
s.saveOutlined('images/result/outline2.png')
def threshold(filename):
m = Thresholding(threshold_value=180,min_width_height=4)
s: ImageManager = ImageManager(filename)
sheeps = []
for x in range(0,255,20):
m.threshold_value = x
s.singleLayerFind(m, 0)
s.saveIntermidiary('images/threshold/{0}-t-image-1.tif'.format(x))
s.outline_mammal(baseImage='rgb')
s.saveOutlined('images/threshold/{0}-o-image-1.png'.format(x))
sheeps.append(len(s.locations))
print(sheeps)
def extracter():
templateSize = 10
template = np.full((templateSize, templateSize), 0, dtype=np.uint8)
template = cv2.circle(template,
(int(templateSize / 2), int(templateSize / 2)), 5,
255, cv2.FILLED)
cv2.imwrite('images/template.png', template)
m = Templating(template, 0.50)
s: ImageManager = ImageManager("images/image3.tif")
s.singleLayerFind(m, 0)
s.extract_sheep("images/extracted")
def miniexample():
template = cv2.imread("images/sheep_(839, 3432).png", cv2.IMREAD_GRAYSCALE)
m = Templating(template, 0.82)
s: ImageManager = ImageManager("images/sheeps.png")
l, intermidary = s.combinedSingleLayerFind(m, [0.299, 0.587, 0.114])
i = intermidary[:, :, 1]
cv2.imwrite("images/sheeps1.png", i)
i = cv2.normalize(i, None, 0, 255, cv2.NORM_MINMAX, cv2.CV_8U)
_, i = cv2.threshold(i, 245, 255, cv2.THRESH_BINARY)
cv2.imwrite("images/sheeps2.png", i)
s.outline_mammal("original")
s.saveOutlined("images/sheeps3.png")
def testTempaltes(filename):
sheeps = []
s: ImageManager = ImageManager(filename)
order = []
for file in os.listdir('images/templates'):
print(file)
template = cv2.imread('images/templates/' + file,cv2.IMREAD_GRAYSCALE)
m = Templating(template, 0.50)
s.singleLayerFind(m, 0)
s.saveIntermidiary('images/template-results/{0}-t-image-1.tif'.format(file))
s.outline_mammal(baseImage='rgb')
s.saveOutlined('images/template-results/{0}'.format(file))
sheeps.append(len(s.locations))
order.append(file)
for x in sheeps:
print(x)
for x in order:
print(x)
def testExtraTemplates(filename):
sheeps = []
order = []
template = cv2.imread(filename, cv2.IMREAD_GRAYSCALE)
print(template.shape)
m = Templating(template, 0.9,False)
for x in range(1,9):
s: ImageManager = ImageManager('images/image-{0}.tif'.format(x))
s.singleLayerFind(m, 0)
s.saveIntermidiary('images/template-results2/{0}.tif'.format(x))
s.outline_mammal(baseImage='rgb')
s.saveOutlined('images/template-results2/image-{0}.png'.format(x))
sheeps.append(len(s.locations))
order.append(x)
for x in sheeps:
print(x)
for x in order:
print(x)
def large_file():
templateSize = 30
template = np.full((templateSize, templateSize), 0, dtype=np.uint8)
#template = cv2.circle(template, (15, 15), 7, 200, cv2.FILLED)
template = cv2.circle(template,
(int(templateSize / 2), int(templateSize / 2)), 5,
255, cv2.FILLED)
#template = cv2.ellipse(img=template, center=(int(templateSize/2), int(templateSize/2)), axes=(4,8),angle=90,startAngle=0,endAngle=360,color=255,thickness=cv2.FILLED)
cv2.imwrite('images/template.png', template)
m = Templating(template, 0.50)
s: ImageManager = ImageManager("images/image3.tif")
s.singleLayerFind(m, 1)
#s.combinedSingleLayerFind(m,[0.299,0.587,0.114])
#s.combinedSingleLayerFind(m, [0.2, 0.2, 0.2, 0.2, 0.2])
#s.multiLayerFind(m)
print(s.locations)
s.saveIntermidiary('images/templating.tif')
s.outline_mammal(padding=10)
s.saveOutlined('images/outlinetemplating.tif')
def thresholding():
if 'filename' not in request.args:
return 'please provide filename argument e.g \\thresholding?filename=example.png',400
if 'threshold' in request.args:
threshold = request.args['threshold']
else:
threshold = 220
m = Thresholding(threshold_value=threshold)
filename = request.args['filename']
filepath = app.root_path + '/' + app.config['UPLOAD_FOLDER'] + '/' + secure_filename(filename)
im: ImageManager = ImageManager(filepath)
im.singleLayerFind(m, 0)
thresholdFile = filename.rsplit('.', 1)[0] + '_threshold.' + filename.rsplit('.', 1)[1]
thresholdFilepath = filepath.rsplit('.', 1)[0] + '_threshold.' + filepath.rsplit('.', 1)[1]
im.saveIntermidiary(thresholdFilepath)
im.outline_mammal()
outlinedFile = filename.rsplit('.', 1)[0] + '_threshold_outlined.' + filename.rsplit('.', 1)[1]
outlinedFilepath = filepath.rsplit('.', 1)[0] + '_threshold_outlined.' + filepath.rsplit('.', 1)[1]
im.saveOutlined(outlinedFilepath)
return render_template('result.html', title='results', intermidaryFile=thresholdFile, outlinedFile=outlinedFile)