def executeCLI(commandString):
print()
print("Executing: {0}".format(commandString))
print()
splitArgs = [item.strip() for item in commandString.split(" ")]
cliHandler(splitArgs) #Run the command
print()
def executeCLI(commandString):
print()
print("Executing: {0}".format(commandString))
print()
splitArgs = [item.strip() for item in commandString.split(" ")]
cliHandler(splitArgs) #Run the command
print()
def detect():
if darkflow.net.yolov2.predict.detection_choice == 1:
arg = [
'flow', '--imgdir', './static/', '--model',
'./cfg/fingertip-yolo.cfg', '--load', '-1', '--batch', '1',
'--threshold', '0.5'
]
elif darkflow.net.yolov2.predict.detection_choice == 2:
arg = [
'flow', '--imgdir', './static/', '--model',
'./cfg/pupils_yolo.cfg', '--load', '-1', '--batch', '1',
'--threshold', '0.9'
]
cliHandler(arg)
def upload_file(request):
if request.method == 'POST':
form = PhotoForm(request.POST, request.FILES)
if form.is_valid():
form.save()
else:
form = PhotoForm()
image_name = request.FILES['photo']
return HttpResponse(cliHandler(image_name))
def upload_file(request):
if request.method == 'POST':
form = PhotoForm(request.POST, request.FILES)
if form.is_valid():
form.save()
return render(request, 'polls/index.html', {'form': form})
else:
form = PhotoForm()
image_name = request.FILES['photo']
return HttpResponse(cliHandler(image_name))
def classify(fileName, decimg):
cliHandler(sys.argv)
openFile = open(fileName)
try:
data = json.load(openFile)
except:
openFile = open("./sample_img/out/none.json")
data = json.load(openFile)
retStr = ''
for i in range(len(data)):
if (data[i]["confidence"] >= 0.6):
retStr += data[i]["label"] + " "
topLeft_x = data[i]["topleft"]["x"]
topLeft_y = data[i]["topleft"]["y"]
bottomRight_x = data[i]["bottomright"]["x"]
bottomRight_y = data[i]["bottomright"]["y"]
cv2.rectangle(decimg, (topLeft_x, topLeft_y),
(bottomRight_x, bottomRight_y), (0, 0, 255), 7)
return retStr, decimg
def upload_file(request):
if request.method == 'POST':
form = PhotoForm(request.POST,request.FILES)
if form.is_valid():
form.save()
print(form)
# return render(request, 'polls/index.html', {'form': form})
else:
form =PhotoForm()
image_name = request.FILES['photo']
fname = 'C:/img/'+str(image_name)
im = Image.open(fname)
im.save('./polls/static/before.jpg')
# im.show()
data, ingre = cliHandler(image_name)
# pd.set_option('colheader_justify', 'center')
# return HttpResponse(cliHandler(image_name))
return render(request, 'polls/upload_file.html')
import sys from darkflow.cli import cliHandler cliHandler(sys.argv)
def flow_data():
image_name = get_image()
cliHandler()
save_data(parse_json(image_name))
cleanup(image_name)
def _execute_yolo(commandstring):
command = [""]+commandstring.split(" ")
print ("executing command",command)
cliHandler(command)
#args.append("bin/yolov2-tiny-voc.weights")
args.append("-1")
args.append("--train")
args.append("--annotation")
args.append("train/annotation")
args.append("--dataset")
args.append("train/ImgPlates")
args.append("--summary")
args.append("summary/")
args.append("--epoch")
args.append("100")
args.append("--batch")
args.append("16")
print("\n\n\n")
for i in args:
print(i, end=" ")
print("\n\n\n")
from darkflow.cli import cliHandler
cliHandler(args)