def run(imagepath):
#
enhancer = Enhancer()
enhancer.enhance(imagepath)
##image = Image.open('pill3.jpg')
##image = ImageEnhance.Contrast(image).enhance(5)
##image.PIL.save("pic.jpg")
##quit()
# get the labels from the Google Vision OCR
vision = Vision()
labels = vision.detect_document(imagepath)
print(labels)
# use Google Vision to detect dominant colors, then extract common color name using a custom library
colors = vision.detect_properties(imagepath)
print(colors)
if len(labels) == 0 or len(colors) == 0:
print('Could not classify')
return 'Unidentified'
api_call = "https://datadiscovery.nlm.nih.gov/resource/crzr-uvwg.json?" + "&splimprint=" + labels[
0]
# concatinate more if there are more than 1 imprints
for i in range(1, len(labels)):
api_call = api_call + ";" + labels[i]
print(api_call)
# make the API GET request
contents = urllib.request.urlopen(api_call).read()
# converts the bytes object to string, then to json
json_response = json.loads(contents.decode())
# get the number of matches
if len(json_response) >= 1:
return json_response[0]['medicine_name']
elif len(json_response) < -1:
json_res = try_with_colors(api_call, colors)
if json_res == None:
return 'Unidentified'
else:
return json_res[0]['medicine_name']
else:
return 'Unidentified'
