def image_to_text(self, imagestream):
result = []
computervision_client = ComputerVisionClient(
self.endpoint, CognitiveServicesCredentials(self.subscription_key))
# Get an image with text
recognize_handw_results = computervision_client.read_in_stream(
imagestream, raw=True)
# Get the operation location (URL with an ID at the end) from the response
operation_location_remote = recognize_handw_results.headers[
"Operation-Location"]
# Grab the ID from the URL
operation_id = operation_location_remote.split("/")[-1]
while True:
get_handw_text_results = computervision_client.get_read_result(
operation_id)
if get_handw_text_results.status not in ['notStarted', 'running']:
break
time.sleep(1)
if get_handw_text_results.status == OperationStatusCodes.succeeded:
for text_result in get_handw_text_results.analyze_result.read_results:
for line in text_result.lines:
result.append(line.text)
return result
def My_OCR(url):
SUBSCRIPTION_KEY = os.getenv('OCR_SUBSCRIPTION_KEY')
ENDPOINT = os.getenv('OCR_ENDPOINT')
CV_CLIENT = ComputerVisionClient(
ENDPOINT, CognitiveServicesCredentials(SUBSCRIPTION_KEY))
ocr_results = CV_CLIENT.read(url, raw=True)
operation_location_remote = ocr_results.headers["Operation-Location"]
operation_id = operation_location_remote.split("/")[-1]
status = ["notStarted", "running"]
while True:
get_handw_text_results = CV_CLIENT.get_read_result(operation_id)
if get_handw_text_results.status not in status:
break
time.sleep(1)
succeeded = OperationStatusCodes.succeeded
text = []
if get_handw_text_results.status == succeeded:
res = get_handw_text_results.analyze_result.read_results
for text_result in res:
for line in text_result.lines:
if len(line.text) <= 8:
text.append(line.text)
r = re.compile("[0-9A-Z]{2,4}[.-]{1}[0-9A-Z]{2,4}")
text = list(filter(r.match, text))
return text[0].replace('.', '-') if len(text) > 0 else ""
def azure_get_data():
subscription_key = "ACCESS KEY"
endpoint = "ENDPOINT URL"
computervision_client = ComputerVisionClient(
endpoint, CognitiveServicesCredentials(subscription_key))
#remote_image_url = "https://raw.githubusercontent.com/MicrosoftDocs/azure-docs/master/articles/cognitive-services/Computer-vision/Images/readsample.jpg"
# Provide the image path
local_image_handwritten_path = "sample4.jpg"
local_image_handwritten = open(local_image_handwritten_path, "rb")
recognize_handwriting_results = computervision_client.read_in_stream(
local_image_handwritten, raw=True)
operation_location_remote = recognize_handwriting_results.headers[
"Operation-Location"]
# Get Operation ID
operation_id = operation_location_remote.split("/")[-1]
# Repeat if Operation ID result status is 'notStarted' or 'running'
while True:
get_handw_text_results = computervision_client.get_read_result(
operation_id)
if get_handw_text_results.status not in ['notStarted', 'running']:
break
time.sleep(1)
# Print the detected text, line by line
if get_handw_text_results.status == OperationStatusCodes.succeeded:
print(type(get_handw_text_results.analyze_result.read_results))
for text_result in get_handw_text_results.analyze_result.read_results:
for line in text_result.lines:
print(line.text)
def extractFromHandwritten(file_name):
# Read the image file
image_path = os.path.join('static', 'uploads', file_name)
image_stream = open(image_path, "rb")
resultString = ""
# Get a client for the computer vision service
computervision_client = ComputerVisionClient(
cog_endpoint, CognitiveServicesCredentials(cog_key))
# Submit a request to read printed text in the image and get the operation ID
read_operation = computervision_client.read_in_stream(image_stream,
raw=True)
operation_location = read_operation.headers["Operation-Location"]
operation_id = operation_location.split("/")[-1]
# Wait for the asynchronous operation to complete
while True:
read_results = computervision_client.get_read_result(operation_id)
if read_results.status not in [OperationStatusCodes.running]:
break
time.sleep(1)
# If the operation was successfuly, process the text line by line
if read_results.status == OperationStatusCodes.succeeded:
for result in read_results.analyze_result.read_results:
for line in result.lines:
resultString += line.text + "\n"
print(line.text)
return resultString
def read_image_text(self, client: ComputerVisionClient, remote_url: str):
"""
read text from an image using the Azure OCR Read API
"""
print(f"Calling read API on {remote_url}")
read_result = client.read(remote_url, raw=True)
operation_location_remote = read_result.headers['Operation-Location']
operation_id = operation_location_remote.split('/')[-1]
# GET method for read results
while True:
read_operation_result = client.get_read_result(operation_id)
if read_operation_result.status not in [
OperationStatusCodes.not_started,
OperationStatusCodes.running]:
break
time.sleep(1) # Re-check every second
return read_operation_result if read_operation_result.status ==\
OperationStatusCodes.succeeded else None
def ocr1(img):
#Cognitive Services endpoint and key
cog_key = '<Your Primary Key here>' #Paste your primary key here
cog_endpoint = '<Endpoint url here>' #Paste your endpoint here
# Get a client for the computer vision service
computervision_client = ComputerVisionClient(
cog_endpoint, CognitiveServicesCredentials(cog_key))
# Submit a request to read printed text in the image and get the operation ID
try:
recognize_handw_results = computervision_client.read(img, raw=True)
except Exception as e:
return str(e)
operation_location_remote = recognize_handw_results.headers[
"Operation-Location"]
operation_id = operation_location_remote.split("/")[-1]
while True:
get_handw_text_results = computervision_client.get_read_result(
operation_id)
if get_handw_text_results.status not in ['notStarted', 'running']:
break
time.sleep(1)
if get_handw_text_results.status == OperationStatusCodes.succeeded:
res = []
for text_result in get_handw_text_results.analyze_result.read_results:
for line in text_result.lines:
res.append(str(line.text))
if res != []:
res = str(" ".join(res)) #Result of OCR
else:
res = None
return res
subscription_key = "7a2607ca622b4e449763a5417111f329"
endpoint = "https://bayern.cognitiveservices.azure.com/"
img_path = 'C:\\Users\\cjjun\\Desktop\\img2.jpg'
client = ComputerVisionClient(endpoint,
CognitiveServicesCredentials(subscription_key))
img = open(img_path, 'rb')
recognize_results = client.read_in_stream(img, raw=True)
img.close()
location_remote = recognize_results.headers["Operation-Location"]
operation_id = location_remote.split("/")[-1]
while True:
result = client.get_read_result(operation_id)
if result.status not in ['notStarted', 'running']:
break
sleep(0.5)
img_text = cv2.imread(img_path)
if result.status == OperationStatusCodes.succeeded:
for text_result in result.analyze_result.read_results:
for line in text_result.lines:
box = [int(i) for i in line.bounding_box]
print(line.text)
for i in range(0, 8, 2):
pt1 = (*box[i:i + 2], )
pt2 = (*box[(i + 2) % 8:(i + 3) % 8 + 1], )
cv2.line(img_text, pt1, pt2, (255, 0, 0), 3)
def InvAns(strUrl):
if 'COMPUTER_VISION_SUBSCRIPTION_KEY' in os.environ:
subscription_key = os.environ['COMPUTER_VISION_SUBSCRIPTION_KEY']
else:
print("\nSet the COMPUTER_VISION_SUBSCRIPTION_KEY environment variable.\n**Restart your shell or IDE for changes to take effect.**")
sys.exit()
if 'COMPUTER_VISION_ENDPOINT' in os.environ:
endpoint = os.environ['COMPUTER_VISION_ENDPOINT']
else:
print("\nSet the COMPUTER_VISION_ENDPOINT environment variable.\n**Restart your shell or IDE for changes to take effect.**")
sys.exit()
computervision_client = ComputerVisionClient(endpoint, CognitiveServicesCredentials(subscription_key))
# print("===== Batch Read File - remote =====")
remote_image_handw_text_url = strUrl
recognize_handw_results = computervision_client.read(remote_image_handw_text_url, raw=True)
operation_location_remote = recognize_handw_results.headers["Operation-Location"]
operation_id = operation_location_remote.split("/")[-1]
while True:
get_handw_text_results = computervision_client.get_read_result(operation_id)
if get_handw_text_results.status not in ['notStarted', 'running']:
break
time.sleep(1)
d = {}
abcA = []
defgA = []
hijA = []
klmA = []
nopA= []
qrsA = []
uvwA = []
flat_list = []
if get_handw_text_results.status == OperationStatusCodes.succeeded:
for text_result in get_handw_text_results.analyze_result.read_results:
for sourceTxt in text_result.lines:
new_d = {}
new_d[sourceTxt.text] = sourceTxt.bounding_box
flat_list.append(sourceTxt.text)
def Get_shipping_in_pdf(sourceTxt):
# print(cf)
shp = r"Shipping.*\d.*$"
shp1 = r"Shipping"
if (re.findall(shp, sourceTxt)):
ans = re.findall(shp, sourceTxt)[0]
f_ans_split = ans.split()
for i in f_ans_split:
if i.isnumeric():
print(i)
f_ans = i
else:
f_ans = ''
elif (re.findall(shp1, sourceTxt)):
f_ans = re.findall(shp1, sourceTxt)[0]
else:
f_ans = "0"
return f_ans
def Get_company_in_pdf(sourceTxt):
frm = r"From:"
frm1 = r"From"
frm2= r"Invoice"
if(re.findall(frm, sourceTxt)):
f_ans = re.findall(frm, sourceTxt)[0]
elif(re.findall(frm1, sourceTxt)):
f_ans = re.findall(frm1, sourceTxt)[0]
elif(re.findall(frm2, sourceTxt)):
f_ans = re.findall(frm2, sourceTxt)[0]
else:
f_ans = 0
# print(f_ans)
return f_ans
def Get_order_in_pdf(sourceTxt):
prcnt = r"Purchase.*\d.*$"
prcnt1 = r"Ord.*\d.*$"
prcnt2 = r"Ord.*\D"
if (re.findall(prcnt, sourceTxt)):
ans = re.findall(prcnt, sourceTxt)[0]
f_ans_split = ans.split()
for i in f_ans_split:
if i.isnumeric():
f_ans = i
else:
f_ans = ''
elif(re.findall(prcnt1, sourceTxt)):
ans = re.findall(prcnt1, sourceTxt)[0]
f_ans_split = ans.split()
for i in f_ans_split:
if i.isnumeric():
f_ans = i
else:
f_ans = ''
elif (re.findall(prcnt2, sourceTxt)):
f_ans = re.findall(prcnt2, sourceTxt)[0]
else:
f_ans = ''
return f_ans
def Get_invoice_in_pdf(sourceTxt):
prcnt = r"Invoice.*\d.*$"
prcnt1 = r"INV.*\-\d.*$"
f_ans = ''
if (re.findall(prcnt1, sourceTxt)):
f_ans = re.findall(prcnt1, sourceTxt)[0]
elif(re.findall(prcnt, sourceTxt)):
ans = re.findall(prcnt, sourceTxt)[0]
f_ans_split = ans.split()
for i in f_ans_split:
if i.isnumeric():
f_ans = i
else:
f_ans = ''
else:
f_ans = ''
return f_ans
def Get_vat_in_document(sourceTxt):
prcnt = r"([0-9][0-9]%$|[0-9]%$)"
if(re.findall(prcnt, sourceTxt)):
f_ans = re.findall(prcnt, sourceTxt)[0]
else:
f_ans = 0
return f_ans
def Get_total_amount_in_pdf(sourceTxt):
lst = r"\d.*,\d{3}\.?\d*$"
dcm = r"\d.*\..?\d*$"
spc = r"\d.*\s\d{3}\.\d*$"
ans=[]
ttl = []
f_ans = []
if(re.findall(lst, sourceTxt)):
ans.extend(re.findall(lst, sourceTxt))
elif re.findall(dcm, sourceTxt):
ans.extend(re.findall(dcm, sourceTxt))
elif re.findall(spc, sourceTxt):
ans.extend(re.findall(spc, sourceTxt))
if ans:
for i in ans:
rem_c = i.split(',')
try:
ttl.append(float("".join(rem_c)))
except ValueError:
pass
if ttl == []:
pass
else:
f_ans.extend(ttl)
return f_ans
def Get_date_in_pdf(sourceTxt):
date_format = [ r"\d{2} (?:%s) \d{4}" % '|'.join(calendar.month_abbr[1:]), r"\d{1} (?:%s) \d{4}" % '|'.join(calendar.month_abbr[1:]), r"\d{2} (?:%s) \d{4}" % '|'.join(calendar.month_name), r"\d{1} (?:%s) \d{4}" % '|'.join(calendar.month_name[1:]), r"(?:%s) \d{2} \d{4}" % '|'.join(calendar.month_abbr[1:]), r"(?:%s) \d{1} \d{4}" % '|'.join(calendar.month_abbr[1:]), r"(?:%s) \d{2} \d{4}" % '|'.join(calendar.month_name), r"(?:%s) \d{1} \d{4}" % '|'.join(calendar.month_name[1:]),r"\d{2} (?:%s), \d{4}" % '|'.join(calendar.month_abbr[1:]), r"\d{1} (?:%s), \d{4}" % '|'.join(calendar.month_abbr[1:]), r"\d{2} (?:%s), \d{4}" % '|'.join(calendar.month_name), r"\d{1} (?:%s), \d{4}" % '|'.join(calendar.month_name[1:]), r"(?:%s) \d{2}, \d{4}" % '|'.join(calendar.month_abbr[1:]), r"(?:%s) \d{1}, \d{4}" % '|'.join(calendar.month_abbr[1:]), r"(?:%s) \d{2}, \d{4}" % '|'.join(calendar.month_name), r"(?:%s) \d{1}, \d{4}" % '|'.join(calendar.month_name[1:])]
dats = []
f_dats = ''
for i in date_format:
if(re.findall(i, sourceTxt)):
dats.extend(re.findall(i, sourceTxt))
else:
ans = re.findall(r'([1-9]|1[0-9]|2[0-9]|3[0-1]|0[0-9])(.|-|\/)([1-9]|1[0-2]|2[0-9]|3[0-9])(.|-|\/)(20[0-9][0-9])',sourceTxt)
ans_f = [''.join(ans[i]) for i in range(len(ans))]
dats.extend(ans_f)
for sublist in dats:
if any(sublist):
f_dats = sublist
break
return f_dats
abc = Get_date_in_pdf(sourceTxt.text)
defg = Get_total_amount_in_pdf(sourceTxt.text)
hij = Get_vat_in_document(sourceTxt.text)
klm = Get_invoice_in_pdf(sourceTxt.text)
nop = Get_order_in_pdf(sourceTxt.text)
qrs = Get_company_in_pdf(sourceTxt.text)
uvw = Get_shipping_in_pdf(sourceTxt.text)
if abc=="" and defg=="" and hij:
continue
elif abc:
abcA.append(abc)
continue
elif defg:
defgA.append(defg)
continue
elif hij:
hijA.append(hij)
elif klm:
klmA.append(klm)
elif nop:
nopA.append(nop)
elif qrs:
print(qrs)
qrsA.append(qrs)
elif uvw:
uvwA.append(uvw)
def get_index_ord(inp, lst):
indx = lst.index(inp)
f_ans = lst[indx + 1]
return f_ans
def get_indx_purchase(inp, lst):
indx = int(lst.index(inp))
f_ans = ''
for i in lst[indx:indx+4]:
if i.isnumeric():
f_ans = i
break
else:
f_ans =''
return f_ans
def get_company_name(inp,lst):
idx = int(lst.index(inp))
f_ans = ''
f_indx = int(idx + 1)
for i in lst[f_indx]:
if i.isnumeric():
f_ans = lst[f_indx + 1]
else:
f_ans = lst[f_indx]
return f_ans
def get_company_name_2(sublist, lst):
f_ans = ''
print(sublist)
if "From:" in sublist:
f_ans = get_company_name("From:", lst)
print(f_ans)
elif "From" in sublist:
f_ans = get_company_name("From", lst)
elif "Invoice" in sublist:
f_ans = get_company_name("Invoice", lst)
else:
f_ans = lst[0]
return f_ans
def Get_shipping_cost(inp, lst):
f_ans = ''
inpt = ''
if inp:
inpt = inp[0]
else:
inpt = "0"
if inpt.isnumeric():
f_ans = inpt
else:
indx = lst.index(inpt)
f_indx = int(indx + 1)
f_ans = lst[f_indx]
if f_ans.isnumeric():
f_ans = lst[f_indx]
else:
f_ans = 0
return f_ans
order_2 = get_index_ord(nopA[0], flat_list)
company_name = get_company_name_2(qrsA, flat_list)
purchase_2 = get_indx_purchase("Invoice", flat_list)
def vat_2(inp):
ans_vat = ''
new_set = list(set([i[0] for i in inp]))
new_set.sort()
if new_set[-1] - new_set[-2] in new_set:
ans_vat = new_set[-1] - new_set[-2]
else:
ans_vat = 0
return ans_vat
vat_2ans = vat_2(defgA)
shipping = int(Get_shipping_cost(uvwA, flat_list))
# print(shipping)
d["date"] = min(abcA)
d["total_amount"] = max(defgA)[0]
d["vat"] = vat_2ans - shipping if int(hijA[0][0:-1]) /100 * d["total_amount"] == 0 else int(hijA[0][0:-1]) /100 * d["total_amount"] - shipping
d["invoice_number"] = klmA[0] if klmA[0] else purchase_2
d["purchase_order_number"] = nopA[0] if nopA[0].isnumeric() else order_2
d["supplier_name"] = company_name
# print("Apiyo", d)
return d
computervision_client = ComputerVisionClient(
endpoint, CognitiveServicesCredentials(subscription_key))
remote_image_handw_text_url = "0.jpg"
# Call API with URL and raw response (allows you to get the operation location)
recognize_handw_results = computervision_client.read(
remote_image_handw_text_url, raw=True)
# Get the operation location (URL with an ID at the end) from the response
operation_location_remote = recognize_handw_results.headers[
"Operation-Location"]
# Grab the ID from the URL
operation_id = operation_location_remote.split("/")[-1]
# Call the "GET" API and wait for it to retrieve the results
while True:
get_handw_text_results = computervision_client.get_read_result(
operation_id)
if get_handw_text_results.status not in ['notStarted', 'running']:
break
time.sleep(1)
results = []
# Print the detected text, line by line
if get_handw_text_results.status == OperationStatusCodes.succeeded:
for text_result in get_handw_text_results.analyze_result.read_results:
for line in text_result.lines:
results.append(line.text)
print("re", results)
# Get an image with text
read_image_url = "https://raw.githubusercontent.com/MicrosoftDocs/azure-docs/master/articles/cognitive-services/Computer-vision/Images/readsample.jpg"
# Call API with URL and raw response (allows you to get the operation location)
read_response = computervision_client.read(read_image_url, raw=True)
# </snippet_read_call>
# <snippet_read_response>
# Get the operation location (URL with an ID at the end) from the response
read_operation_location = read_response.headers["Operation-Location"]
# Grab the ID from the URL
operation_id = read_operation_location.split("/")[-1]
# Call the "GET" API and wait for it to retrieve the results
while True:
read_result = computervision_client.get_read_result(operation_id)
if read_result.status not in ['notStarted', 'running']:
break
time.sleep(1)
# Print the detected text, line by line
if read_result.status == OperationStatusCodes.succeeded:
for text_result in read_result.analyze_result.read_results:
for line in text_result.lines:
print(line.text)
print(line.bounding_box)
print()
# </snippet_read_response>
'''
END - Read File - remote
'''
def main():
tello = Tello()
tello.connect()
tello.streamon()
frame_read = tello.get_frame_read()
tello.takeoff()
time.sleep(4)
tello.send_rc_control(0, 0, 70, 0)
time.sleep(1.5)
tello.send_rc_control(0, 0, 0, 0)
try:
# Configure Azure Computer vision
computervision_client = ComputerVisionClient(
COGNITIVESVC_ENDPOINT,
CognitiveServicesCredentials(SUBSCRIPTION_KEY))
# Configure MediaPipe hands recognizer
mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands
hands = mp_hands.Hands(max_num_hands=2,
min_detection_confidence=0.8,
min_tracking_confidence=0.5)
while True:
# Get frame
original_frame = frame_read.frame
frame = cv2.flip(original_frame, 1)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
frame.flags.writeable = False # Enabled pass by reference and improves performance
num_of_fingers = -1
results = hands.process(frame)
if results.multi_hand_landmarks:
for hand_landmarks in results.multi_hand_landmarks:
mp_drawing.draw_landmarks(frame, hand_landmarks,
mp_hands.HAND_CONNECTIONS)
num_of_fingers = num_of_fingers + count_finger(
hand_landmarks, mp_hands.HandLandmark.PINKY_MCP,
mp_hands.HandLandmark.THUMB_TIP,
mp_hands.HandLandmark.THUMB_IP)
num_of_fingers = num_of_fingers + count_finger(
hand_landmarks, mp_hands.HandLandmark.WRIST,
mp_hands.HandLandmark.INDEX_FINGER_TIP,
mp_hands.HandLandmark.INDEX_FINGER_PIP)
num_of_fingers = num_of_fingers + count_finger(
hand_landmarks, mp_hands.HandLandmark.WRIST,
mp_hands.HandLandmark.MIDDLE_FINGER_TIP,
mp_hands.HandLandmark.MIDDLE_FINGER_PIP)
num_of_fingers = num_of_fingers + count_finger(
hand_landmarks, mp_hands.HandLandmark.WRIST,
mp_hands.HandLandmark.RING_FINGER_TIP,
mp_hands.HandLandmark.RING_FINGER_PIP)
num_of_fingers = num_of_fingers + count_finger(
hand_landmarks, mp_hands.HandLandmark.WRIST,
mp_hands.HandLandmark.PINKY_TIP,
mp_hands.HandLandmark.PINKY_PIP)
print("Number of fingers: " + str(num_of_fingers))
# Show image
cv2.imshow('Webcam', frame)
# Exit when user press ESC key
k = cv2.waitKey(3) & 0xFF
if k == 27: # ESC Key
break
tello.send_rc_control(0, 0, 0, 0)
time.sleep(1)
if num_of_fingers > 0 and num_of_fingers < 10:
while num_of_fingers > 0:
# Get frame
ocr_frame = frame_read.frame
ocr_frame.flags.writeable = False
# Send frame to Microsoft Azure Cognitive Services to detect text in the image
_, buf = cv2.imencode(".jpg", ocr_frame)
stream = io.BytesIO(buf)
recognize_handw_results = computervision_client.read_in_stream(
stream, raw=True)
# OCR is async. Wait until is completed.
operation_location_remote = recognize_handw_results.headers[
"Operation-Location"]
operation_id = operation_location_remote.split("/")[-1]
while True:
get_handw_text_results = computervision_client.get_read_result(
operation_id)
if get_handw_text_results.status not in [
'notStarted', 'running'
]:
break
tello.send_rc_control(0, 0, 0, 0)
time.sleep(1)
# Mark the detected text, line by line
xg = yg = wg = hg = None
if get_handw_text_results.status == OperationStatusCodes.succeeded:
for text_result in get_handw_text_results.analyze_result.read_results:
for line in text_result.lines:
for word in line.words:
boundingbox = word.bounding_box
if str(num_of_fingers) in word.text:
xg, yg, wg, hg = (int(boundingbox[0]),
int(boundingbox[1]),
int(boundingbox[2] -
boundingbox[0]),
int(boundingbox[7] -
boundingbox[1]))
cv2.rectangle(ocr_frame, (xg, yg),
(xg + wg, yg + hg),
(0, 255, 0), 2)
else:
nxg, nyg, nwg, nhg = (
int(boundingbox[0]),
int(boundingbox[1]),
int(boundingbox[2] -
boundingbox[0]),
int(boundingbox[7] -
boundingbox[1]))
cv2.rectangle(ocr_frame, (nxg, nyg),
(nxg + nwg, nyg + nhg),
(0, 0, 255), 2)
cv2.imshow('Webcam', ocr_frame)
# Exit when user press ESC key
k = cv2.waitKey(3) & 0xFF
if k == 27: # ESC Key
break
velocity_fb = velocity_lr = velocity_ud = velocity_yaw = 0
if not xg is None:
# Move the drone
object_center_x = int(xg + (wg / 2))
object_center_y = int(yg + (hg / 2))
object_size = ((wg**2) + (hg**2))**0.5 # Fast sqrt
object_distance = DESIRED_OBJECT_SIZE - object_size
if not object_distance == 0:
velocity_fb = int(
MAX_SPEED_FORWARDBACK *
(object_distance / DESIRED_OBJECT_SIZE))
frame_shape = ocr_frame.shape
# I wrote 'object_center_y + 200' because the camera of Tello drone is slightly inclined to down and that causes the drone to go too high
velocity_ud = calculate_velocity(
frame_shape[1], object_center_y + 200,
MAX_SPEED_UPDOWN * -1)
velocity_lr = calculate_velocity(
frame_shape[0], object_center_x, MAX_SPEED_LR)
if abs(velocity_fb) < 5 and abs(
velocity_ud) < 5 and abs(velocity_yaw) < 5:
time.sleep(5)
break
if not velocity_lr == velocity_fb == velocity_ud == velocity_yaw == 0:
tello.send_rc_control(velocity_lr, velocity_fb,
velocity_ud, velocity_yaw)
time.sleep(MOV_TIME)
tello.send_rc_control(0, 0, 0, 0)
finally:
tello.land()
tello.streamoff()
tello.end()
# When everything done, release the capture
cv2.destroyAllWindows()
print("===== Read File - local =====")
# Get image of handwriting
local_image_handwritten_path = os.path.join (images_folder, "handwritten_text.jpg")
# Open the image
local_image_handwritten = open(local_image_handwritten_path, "rb")
# Call API with image and raw response (allows you to get the operation location)
recognize_handwriting_results = computervision_client.read_in_stream(local_image_handwritten, raw=True)
# Get the operation location (URL with ID as last appendage)
operation_location_local = recognize_handwriting_results.headers["Operation-Location"]
# Take the ID off and use to get results
operation_id_local = operation_location_local.split("/")[-1]
# Call the "GET" API and wait for the retrieval of the results
while True:
recognize_handwriting_result = computervision_client.get_read_result(operation_id_local)
if recognize_handwriting_result.status.lower () not in ['notstarted', 'running']:
break
print ('Waiting for result...')
time.sleep(10)
# Print results, line by line
if recognize_handwriting_result.status == OperationStatusCodes.succeeded:
for text_result in recognize_handwriting_result.analyze_result.read_results:
for line in text_result.lines:
print(line.text)
print(line.bounding_box)
print()
'''
END - Read File - local
'''
# Call API with URL and raw response (allows you to get the operation location)
recognize_printed_results = computervision_client.read(
remote_image_printed_text_url, language='en', raw=True)
# </snippet_read_call>
# <snippet_read_response>
# Get the operation location (URL with an ID at the end) from the response
operation_location_remote = recognize_printed_results.headers[
"Operation-Location"]
# Grab the ID from the URL
operation_id = operation_location_remote.split("/")[-1]
# Call the "GET" API and wait for it to retrieve the results
while True:
get_printed_text_results = computervision_client.get_read_result(
operation_id)
if get_printed_text_results.status not in ['NotStarted', 'Running']:
break
time.sleep(1)
# Print the detected text, line by line
if get_printed_text_results.status == TextOperationStatusCodes.succeeded:
for text_result in get_printed_text_results.recognition_results:
for line in text_result.lines:
print(line.text)
print(line.bounding_box)
print()
# </snippet_read_response>
'''
END - Batch Read File - remote
'''
def azure_batch_read_in_stream(filename=None, callOCR=True, verbose=False):
"""RecognizeTextUsingBatchReadAPI.
This will recognize text of the given image using the Batch Read API.
"""
import time
#
# Azure Specific
#
SUBSCRIPTION_KEY_ENV_NAME = os.environ.get(
"COMPUTERVISION_SUBSCRIPTION_KEY", None)
COMPUTERVISION_LOCATION = os.environ.get("COMPUTERVISION_LOCATION",
"westeurope")
azure_client = ComputerVisionClient(
endpoint="https://" + COMPUTERVISION_LOCATION +
".api.cognitive.microsoft.com/",
credentials=CognitiveServicesCredentials(SUBSCRIPTION_KEY_ENV_NAME))
print("AZURE Image Name {}".format(filename))
p = Path(filename)
(imgname, imgext) = os.path.splitext(p.name)
# Check if we have a cached ocr response already for this provider
invokeOCR = callOCR
if not callOCR:
if not os.path.exists(
os.path.join(RESULTS_FOLDER, imgname + ".azure.read.json")):
invokeOCR = True
if invokeOCR:
# Azure Computer Vision Call
# with open(os.path.join(IMAGES_FOLDER, filename), "rb") as image_stream:
with open(filename, "rb") as image_stream:
job = azure_client.read_in_stream(image=image_stream, raw=True)
operation_id = job.headers['Operation-Location'].split('/')[-1]
image_analysis = azure_client.get_read_result(operation_id, raw=True)
while image_analysis.output.status in ['notstarted', 'running']:
time.sleep(1)
image_analysis = azure_client.get_read_result(
operation_id=operation_id, raw=True)
print("\tJob completion is: {}".format(image_analysis.output.status))
print("\tRecognized {} page(s)".format(
len(image_analysis.output.analyze_result.read_results)))
with open(os.path.join(RESULTS_FOLDER, imgname + ".azure.read.json"),
'w') as outfile:
outfile.write(image_analysis.response.content.decode("utf-8"))
ocrresponse = image_analysis.response.content.decode("utf-8")
else:
# Use local OCR cached response when available
with open(os.path.join(RESULTS_FOLDER, imgname + ".azure.read.json"),
'r') as cachefile:
ocrresponse = cachefile.read().replace('\n', '')
# Convert the original ocrresponse into proper object
ocrresponse = BBOXOCRResponse.from_azure(json.loads(ocrresponse))
# load the original response to get the text as-is
original_text = ""
for page in ocrresponse.pages:
for line in page.lines:
original_text += (line.text)
original_text += ('\n')
with open(os.path.join(RESULTS_FOLDER, imgname + ".before.azure.read.txt"),
'w') as outfile:
outfile.write(original_text)
# Create BBOX OCR Response from Azure CV string response
bboxresponse = BBoxHelper(
verbose=verbose).processAzureOCRResponse(ocrresponse)
with open(os.path.join(RESULTS_FOLDER, imgname + ".azure.bbox.json"),
'w') as outfile:
outfile.write(
json.dumps(bboxresponse.__dict__,
default=lambda o: o.__dict__,
indent=4))
with open(os.path.join(RESULTS_FOLDER, imgname + ".after.azure.read.txt"),
'w') as outfile:
outfile.write(bboxresponse.text)
return (original_text, bboxresponse.text)
