def image_listen(request, image_id):
global rootdir, segdir, enddir, count
kandb = KanDB.objects.using('postgresql').all()
myobject = DocumentImage.objects.get(pk=image_id)
image_path = myobject.image_url.url
image_path = os.path.join('web_app/hwrkannada/hwrkannada',
image_path[1:len(image_path)])
path = os.path.join(os.path.dirname(__file__), '../../../')
os.chdir(path)
sys.path.insert(0, os.getcwd())
from main import segmentation_call
rootdir, segdir = segmentation_call(image_path)
enddir = segdir.split('/images/')[1]
imagelist = os.listdir(segdir + "/lines")
imagelist.sort()
from main import prediction_call, augmentation_call
augdir = augmentation_call(image_path, segdir)
template = loader.get_template('image_listen.html')
output = prediction_call(augdir)
# The output is parsed and results page is rendered to show the output
output = output[0]
output = output.replace(" ", "")
h = html.parser.HTMLParser()
h.unescape(output)
#print("op",output)
#print("kandb",kandb[count].kannada)
#myobject = DocumentImage.objects.get(pk=image_id)
context = {
'image_id': image_id,
'myobject': myobject,
'output': output,
'kandb': kandb[count],
}
if (output == kandb[count].kannada):
print("True")
count = count + 1
return HttpResponse(template.render(context, request))
def post(self, request):
global rootdir, segdir, enddir
#thumbnail = request.FILES.get('file', False)
#thumbnail = request.FILES#["Image"]
#form = DocumentForm(request.POST, request.FILES)
thumbnail = request.FILES #["Image"]
form = DocumentForm(request.POST, thumbnail)
if form.is_valid():
form.save()
else:
print("Not valid")
#latest_image = DocumentImage.objects.order_by('-pub_date')[:1]
latest_image = DocumentImage.objects.order_by('-pub_date')[:1]
for image in latest_image:
#print(latest_image)
image_id = image.image_id
myobject = DocumentImage.objects.get(pk=image_id)
#kandb = KanDB.objects.using('postgresql').all()
print(myobject.image_url.url)
image_path = myobject.image_url.url
image_path = os.path.join('web_app/hwrkannada/hwrkannada',
image_path[1:len(image_path)])
path = os.path.join(os.path.dirname(__file__), '../../../')
os.chdir(path)
sys.path.insert(0, os.getcwd())
from main import segmentation_call
rootdir, segdir = segmentation_call(image_path)
enddir = segdir.split('/images/')[1]
imagelist = os.listdir(segdir + "/lines")
imagelist.sort()
from main import prediction_call, augmentation_call
augdir = augmentation_call(image_path, segdir)
output = prediction_call(augdir)
# The output is parsed and results page is rendered to show the output
output = output[0]
output = output.replace(" ", "")
print(output)
return Response({"output": output})
def linesegments(request, image_id):
global rootdir, segdir, enddir
template = loader.get_template('hwrapp/linesegments.html')
myobject = DocumentImage.objects.get(pk=image_id)
# Image path of selected image which is to be sent to module for processing
image_path = myobject.image_url.url
image_path = os.path.join('web_app/hwrkannada/hwrkannada',
image_path[1:len(image_path)])
path = os.path.join(os.path.dirname(__file__), '../../../')
os.chdir(path)
sys.path.insert(0, os.getcwd())
from main import segmentation_call
rootdir, segdir = segmentation_call(image_path)
enddir = segdir.split('/images/')[1]
imagelist = os.listdir(segdir + "/lines")
imagelist.sort()
context = {'image_id': image_id, 'enddir': enddir, 'imagelist': imagelist}
return HttpResponse(template.render(context, request))