def test_one_car(self):
car1 = Car(description='car1',
engine='2L',
year=2015,
make='Honda',
owner='Chris',
photo=self.img)
car1.save()
cars = Car.objects.all()
self.assertEqual(len(cars), 1)
def test_one_car(self):
car1 = Car(description='car1',
engine='2L',
year=2015,
make='Honda',
owner='Chris',
photo=self.img)
car1.save()
cars = Car.objects.all()
self.assertEqual(len(cars), 1)
def get(self, request):
result = []
car = request.GET.get("car")
car = Car.get_by_id(car)
odata = Spares.objects.filter(model=car)
nodata = SparesAnalog.objects.filter(model=car)
for d in odata:
result.append(
{
"name": d.name.name,
"part_number": d.part_number,
"cost": d.cost,
"count": d.count,
"type": "Оригинал",
}
)
for nd in nodata:
result.append(
{
"name": nd.name.name,
"part_number": nd.part_number,
"cost": nd.cost,
"count": nd.count,
"type": "Аналог",
}
)
return render(request, "spares/index.html", {"result": result})
def post(self, request):
car = Car(owner=request.user)
form = self.form(data=request.POST, instance=car)
if form.is_valid():
form.save()
response = HttpResponseRedirect(reverse('cars'))
msg_level = messages.SUCCESS
msg = _('Congrats! Now we are keeping your.car!\
Add some data about it.')
messages.add_message(request, msg_level, msg)
else:
context = {'form': form}
first_contact = request.POST.get('first_contact')
if not first_contact:
template = "car/car_list.html"
else:
template = "car/new_car_get_started.html"
msg_level = messages.ERROR
msg = _('You have some problems on your car info. \
Please, correct these trying to create it again.')
messages.add_message(request, msg_level, msg)
response = TemplateResponse(request, template, context)
return response
def test_handle_with_car_not_found(self, send_message_mock, car_mock):
car_mock.side_effect = Car.DoesNotExist()
chat_id = 1
plate = 'ABC9876'
self.inform_command.handle(chat_id, plate)
car_mock.assert_called_with(license_plate=plate)
text = 'No car with license plate %s found.' % plate
message = {'chat_id': chat_id, 'text': text}
send_message_mock.assert_called_with(message)
def AddCars():
if request.method=='POST':
name=request.form.get('name')
car_type=request.form.get('type')
price=request.form.get('price')
image_url=request.form.get('image_url')
new_car=Car(name=name,car_type=car_type,hire_price=price,image_url=image_url,owner=current_user)
db.session.add(new_car)
db.session.commit()
flash('Added Successfully')
return redirect('/cars')
return render_template('mycars.html')
def post(self, request, *args, **kwargs):
serialize_data = self.get_serializer(data=request.data)
if serialize_data.is_valid():
file = serialize_data.validated_data['file']
xl = pd.ExcelFile(file)
df = xl.parse(xl.sheet_names[0])
for index, row in df.iterrows():
if isinstance(row['date'], str):
date = datetime.strptime(row['date'], '%d/%m/%Y')
else:
date = row['date']
if date.year < 1900:
date = jdatetime.date(day=date.day,
month=date.month,
year=date.year).togregorian()
name = row['name']
price = row['price']
total = row['total']
try:
car = Car.objects.get(name=name)
except Car.DoesNotExist as e:
car = Car(name=name)
car.save()
car_stock = CarStock(car=car,
price=price,
total=total,
date=date)
car_stock.save()
data = {}
return responses.SuccessResponse(data, status=200).send()
else:
dev_error = serialize_data.errors
message = 'Failed to upload {}'.format(
serialize_data.data['file'].name)
return responses.ErrorResponse(message=message,
dev_error=dev_error,
status=400).send()
def get(self, request):
result = {}
result["spares"] = []
result["original"] = True
car = request.GET.get("car")
id = request.GET.get("id")
if id:
cr = Car.get_by_id(car)
original_cost = 0
analog_cost = 0
wrk = Work.get_by_id(id=id)
for sc in SparesOriginalCount.objects.filter(work__id=id).order_by("name"):
original_cost = original_cost + (sc.name.cost * sc.count)
if not self.CHECK.get(request.GET.get("original")):
continue
result["spares"].append(
{
"id": sc.name.id,
"name": sc.name.name.name,
"part_number": sc.name.part_number,
"cost": sc.name.cost,
"count": sc.count,
"type": "Оригинал",
}
)
for notsc in SparesAnalogCount.objects.filter(work__id=id).order_by("name"):
analog_cost = analog_cost + (notsc.name.cost * notsc.count)
if self.CHECK.get(request.GET.get("original")):
continue
result["spares"].append(
{
"id": notsc.name.id,
"name": notsc.name.name.name,
"part_number": notsc.name.part_number,
"cost": notsc.name.cost,
"count": notsc.count,
"type": "Аналог",
}
)
cost = original_cost
if not self.CHECK.get(request.GET.get("original")):
cost = analog_cost
result["original"] = False
result["spares_cost"] = cost
result["work_cost"] = cr.model.brand.clock_rate * wrk.work_ratio
result["difference"] = original_cost - analog_cost
result["summary"] = cr.model.brand.clock_rate * wrk.work_ratio + cost
return render(request, "work/index.html", {"result": result})
return JsonResponse({"success": False, "result": result})
def add_car(request):
book_id = request.POST.get('book_id')
book_count = int(request.POST.get('book_count'))
print('add_car', book_count)
print('add_car', book_id)
# 字典方式存储book
# book_list= []
# book_list.append({"id":book_id})
# request.session['car'] = book_list
car = request.session.get('car')
txtUsername = request.session.get('txtUsername')
if txtUsername:
user = TUser.objects.get(user_name=txtUsername)
user_car = TCar.objects.filter(id=user.user_id)
for user_book in user_car:
if int(book_id) == user_book.book_id:
try:
user_book.goods_number = int(
user_book.goods_number) + book_count
user_book.save()
print(user_book.goods_number)
except:
print('update error')
if car:
car.add(book_id, book_count)
request.session['car'] = car
for res in car.book_list:
print(res.id, res.name, res.count, res.price, res.picture)
else:
car = Car()
car.add(book_id, book_count)
request.session['car'] = car
for res in car.book_list:
print(res.id, res.name, res.count, res.price, res.picture)
return HttpResponse('添加成功')
def get(self, request):
def sortdict(dct):
res = OrderedDict()
for x in sorted(dct):
for k, v in dct.items():
if k == x:
res[k] = v
return res
result = {}
car = request.GET.get("car")
car = Car.get_by_id(car)
for wrk in Work.objects.filter(active=True, cars=car):
if result.get(wrk.type_work.name):
result[wrk.type_work.name].append({
"id": wrk.id,
"name": wrk.name
})
else:
result[wrk.type_work.name] = [{"id": wrk.id, "name": wrk.name}]
return JsonResponse({"success": True, "result": sortdict(result)})
def car(request):
txtUsername = request.session.get('txtUsername')
# 登录
if txtUsername:
car = request.session.get('car')
user = TUser.objects.get(user_name=txtUsername)
user_car = TCar.objects.filter(id=user.user_id)
# 外面有车
if car:
if request.session.get('car'):
for book in car.book_list:
flag = False
for user_book in user_car:
if int(book.id) == user_book.book_id:
try:
with transaction.atomic():
if int(user_book.goods_number) > int(
book.count):
pass
else:
user_book.goods_number = int(
book.count)
user_book.save()
flag = True
except:
print('update error')
if not flag:
try:
with transaction.atomic():
TCar.objects.create(book_id=book.id,
goods_number=book.count,
id=user)
except:
print('insert1 error')
else:
for book in car.book_list:
try:
with transaction.atomic():
TCar.objects.create(book_id=book.id,
goods_number=book.count,
id=user)
except:
print('insert2 error')
for user_book in user_car:
flag = False
for book in car.book_list:
if int(book.id) == user_book.book_id:
book.count = int(user_book.goods_number)
flag = True
if not flag:
car.add(user_book.book_id, user_book.goods_number)
request.session['car'] = car
sum_price = 0
sum_count = 0
for i in car.book_list:
sum_price = sum_price + float(i.price) * int(i.count)
sum_count = sum_count + int(i.count)
return render(
request, 'dangdang/car.html', {
'txtUsername': txtUsername,
'car': car,
'sum_price': sum_price,
'sum_count': sum_count
})
else:
car = Car()
for user_book in user_car:
print(user_book.book_id, user_book.goods_number)
car.add(user_book.book_id, user_book.goods_number)
print(car)
request.session['car'] = car
sum_price = 0
sum_count = 0
for i in car.book_list:
sum_price = sum_price + float(i.price) * int(i.count)
sum_count = sum_count + int(i.count)
return render(
request, 'dangdang/car.html', {
'car': car,
'sum_price': sum_price,
'sum_count': sum_count,
'txtUsername': txtUsername
})
elif request.session.get('car'):
car = request.session.get('car')
sum_price = 0
sum_count = 0
for i in car.book_list:
sum_price += i.price * i.count
sum_count += i.count
return render(request, 'dangdang/car.html', {
'car': car,
'sum_price': sum_price,
'sum_count': sum_count
})
# 未登录 外面无车
else:
car = request.session.get('car')
return render(request, 'dangdang/car.html', {'car': car})
def Wls(video, start_time, location, latitude, longtitude):
""""""
savePath = video
video = 'static/videos/'+video
uploaded_time = 0.0
baseline_01 = 0.55
baseline_02 = 1.0
writer = None
frame_per_second = 30
maxLost = 3 # maximum number of object losts counted when the object is being tracked
car_label_strlist = np.loadtxt("Module/car_label2.csv", delimiter=',', dtype='str')
#load vgg16
pre_model = VGG16(weights='imagenet', include_top=False, input_shape=(224, 224, 3), backend=keras.backend,
layers=keras.layers, models=keras.models, utils=keras.utils)
pre_model.trainable = True
pre_model.summary()
# add output layer for VGG16 output (4096 -> 1000 => 4096 -> 1000 -> 100)
vgg_model = models.Sequential()
vgg_model.add(pre_model)
vgg_model.add(layers.Flatten())
vgg_model.add(layers.Dense(4096, activation='relu'))
vgg_model.add(layers.Dense(1024, activation='relu'))
vgg_model.add(layers.Dense(20, activation='softmax')) # practical
vgg_model.summary()
vgg_model.compile(loss='categorical_crossentropy', optimizer=optimizers.RMSprop(lr=2e-5), metrics=['acc'])
#vgg_model.load_weights("y_s_weights.h5") # 가중치 모델 1
#vgg_model.load_weights("y_up_weights.h5") # 가중치 모델 2
vgg_model.load_weights("Module/CarDatabaseShare/y_seventh_car_weight.hdf5") #가중치 모델 3
# Load Yolo
net = cv.dnn.readNet("Module/CarDatabaseShare/yolov3.weights", "Module/CarDatabaseShare/yolov3.cfg")
classes = []
with open("Module/CarDatabaseShare/coco.names", "r") as f:
classes = [line.strip() for line in f.readlines()]
layer_names = net.getLayerNames()
output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]
#print(len(classes))
colors = np.random.uniform(0, 255, size=(len(classes), 3))
#print(colors)
bbox_colors = np.random.randint(0, 255, size=(len(classes), 3))
#print(bbox_colors)
tracker = Tracker(maxLost=maxLost)
cap = cv.VideoCapture(video)
# Check if camera opened successfully
if not cap.isOpened():
print("Error opening video stream or file")
sys.exit()
vwidth = cap.get(3) # float
vheight = cap.get(4) # float
frame_count = 0
while True:
_, frame = cap.read()
if _ is not True:
break
height, width, channels = frame.shape
# Detecting objects
blob = cv.dnn.blobFromImage(frame, 0.00392, (320, 320), (0, 0, 0), True, crop=False)
net.setInput(blob)
outs = net.forward(output_layers)
# Showing informations on the screen
class_ids = []
confidences = []
boxes = []
detected_boxes = []
detected_label = []
detected_times = []
detected_colors = []
for out in outs:
for detection in out:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > 0.5:
# Object detected
center_x = int(detection[0] * width)
center_y = int(detection[1] * height)
w = int(detection[2] * width)
h = int(detection[3] * height)
# Rectangle coordinates
x = int(center_x - w / 2)
y = int(center_y - h / 2)
boxes.append([x, y, w, h])
confidences.append(float(confidence))
class_ids.append(class_id)
indexes = cv.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
# print(indexes)
font = cv.FONT_HERSHEY_PLAIN
for i in range(len(boxes)):
if i in indexes:
x, y, w, h = boxes[i]
if h > 40 and w > 50 and class_ids[i] == 2 and y > (vheight * baseline_01) and (y + h) < (vheight * baseline_02):
cropimg = frame.copy()
cropimg = frame[y:y+h, x:x+w]
try:
colorlabel = process_image(cropimg)
cropimg = cv.cvtColor(cropimg, cv.COLOR_BGR2GRAY)
cropimg = cv.resize(cropimg, dsize=(224, 224), interpolation=cv.INTER_AREA)
cropimg = cv.GaussianBlur(cropimg, (3, 3), 0)
cannimg = cv.Canny(cropimg, 25, 50)
npimg = np.asarray(cannimg)
npimg = np.stack((cannimg,)*3, axis=-1)
npimg = np.expand_dims(npimg, axis=0)
#print(npimg.shape)
car_recog = CarClassifier(npimg, vgg_model, car_label_strlist)
detected_boxes.append((x, y, x + w, y + h))
detected_label.append(car_recog)
detected_times.append(int(frame_count/frame_per_second) + 1)
detected_colors.append(colorlabel)
except:
continue
color = colors[i]
cv.rectangle(frame, (x, y), (x + w, y + h), color, 2)
#cv.putText(frame, car_recog, (x, y + 30), font, 2, color, 3)
#cv.putText(frame, label, (x, y + 20), font, 3, color, 3)
elif (class_ids[i] == 3 or class_ids[i] == 5 or class_ids[i] == 7) and y > (vheight * baseline_01) and (y + h) < (vheight * baseline_02):
cropimg = frame.copy()
cropimg = frame[y:y+h, x:x+w]
colorlabel = process_image(cropimg)
label = str(classes[class_ids[i]])
color = colors[i]
cv.rectangle(frame, (x, y), (x + w, y + h), color, 2)
#cv.putText(frame, label, (x, y + 20), font, 2, color, 3)
detected_boxes.append((x, y, x + w, y + h))
detected_label.append(label)
detected_times.append(int(frame_count/frame_per_second) + 1)
detected_colors.append(colorlabel)
cv.line(frame, (0,int(vheight*baseline_01)), (int(vwidth-1), int(vheight*baseline_01)), (0,0,0), 2)
cv.line(frame, (0, int(vheight * baseline_02)), (int(vwidth - 1), int(vheight * baseline_02)), (0, 0, 0), 2)
objects = tracker.update(detected_boxes, detected_label, detected_times, detected_colors) # update tracker based on the newly detected objects
for (objectID, centroid) in objects.items():
text = "ID {}".format(objectID)
if centroid[1] > (vheight * baseline_01) and centroid[1] < (vheight * baseline_02):
cv.putText(frame, text, (centroid[0] - 10, centroid[1] - 10), cv.FONT_HERSHEY_SIMPLEX,
0.5, (0, 255, 0), 2)
cv.circle(frame, (centroid[0], centroid[1]), 4, (0, 255, 0), -1)
# cv.imshow('', frame)
key = cv.waitKey(1)
if key == 27:
break
if writer is None:
startTime = start_time.replace(" ", "-")
startTime = startTime.replace(":", "-")
savepath=savePath.split(".")[0]
filePath= "static/output/" + savepath + "-" + startTime + ".mp4"
print(filePath)
fourcc = cv.VideoWriter_fourcc(*"h264")
# fourcc = cv.VideoWriter_fourcc(*"mp4v")
writer = cv.VideoWriter(filePath, fourcc, 30, (int(vwidth), int(vheight)), True)
writer.write(frame)
if frame_count % 50 == 0:
classified_info_list = tracker.getClassifiedInfo()
for obj in classified_info_list:
print(obj)
frame_count+=1
cctv = Cctv(video_link=filePath, location=location, start_time=start_time, latitude=latitude, longtitude=longtitude)
cctv.save()
classified_info_list = tracker.getClassifiedInfo()
for obj in classified_info_list:
print(obj)
#car model 이름 나오게하기, appearance_time 에다가 초 더하기, 브랜드 넣으면 좋음
#CCTV video_link 제대로 넣기 // 했고
for obj in classified_info_list:
try:
model_brand = obj[1][0][0].split("-")
model = model_brand[0]
brand = model_brand[1]
except:
model = obj[1][0][0]
brand = obj[1][0][0]
try:
car = Car.objects.get(model=model)
# car = Car.objects.get(model='a')
except:
car = Car(model=model, brand=brand)
# car = Car(model='a', brand="")
car.save()
start_time = datetime.datetime.strptime(str(start_time), '%Y-%m-%d %H:%M:%S')
appearance_time = start_time + timedelta(seconds=obj[2])
cctv_log = CctvLog(car_model=car, color=obj[3], appearance_time=appearance_time, cctv_id=cctv)
cctv_log.save()
writer.release()
cap.release()
os.remove(video)
cv.destroyAllWindows()