async def create_upload_file(file: UploadFile = File(...)):
file_name = file.filename
file.save('./{}'.format(file_name))
packets = rdpcap('./{}'.format(file_name))
res = {}
data = []
# Let's iterate through every packet
for packet in packets:
res = {
'Ethernet': {
'dst': '{}'.format(packet.sprintf("%Ether.dst%")),
'src': '{}'.format(packet.sprintf("%Ether.src%")),
'type': '{}'.format(packet.sprintf("%Ether.type%"))
},
'ARP': {
'hwtype': '{}'.format(packet.sprintf("%ARP.hwtype%")),
'ptype': '{}'.format(packet.sprintf("%ARP.ptype%")),
'hwlen': '{}'.format(packet.sprintf("%ARP.hwlen%")),
'plen': '{}'.format(packet.sprintf("%ARP.plen%")),
'op': '{}'.format(packet.sprintf("%ARP.op%")),
'hwsrc': '{}'.format(packet.sprintf("%ARP.hwsrc%")),
'psrc': '{}'.format(packet.sprintf("%ARP.psrc%")),
'hwdst': '{}'.format(packet.sprintf("%ARP.hwdst%")),
'pdst': '{}'.format(packet.sprintf("%ARP.pdst%"))
},
'Padding': {
'load': '{}'.format(packet.sprintf("%Padding.load%"))
}
}
data.append(res)
return data
def upload_waybillimg(request: Request, waybillNo: str, file: UploadFile = File(...),):
referrer = request.headers.get("Referer")
print('upload_image()-request.url: %s \t referrer: %s' % (request.url, referrer))
# if 'file' not in file. request.files:
if len(file) < 1 :
flash('No file part')
return RedirectResponse(referrer)
# file = request.files['file']
print("file tag", file)
if file.filename == '':
flash('No image selected for uploading')
return RedirectResponse(referrer)
default_wbNo = 'waybillNo'
# waybillNo = request.form.get('waybillNo', default_wbNo)
info = ['NA', 'NA', 'NA', 'NA']
for wb in waybillList:
if waybillNo == wb[0]:
info = wb
if file and allowed_file(file.filename):
original_filename = secure_filename(file.filename)
file_ext = '.' + (original_filename.rsplit('.', 1)[1].lower().__str__())
print('from referrer %s waybillno %s' % (referrer, waybillNo))
saving_filename = waybillNo + file_ext
unique_filename = make_unique(saving_filename)
# file.save(os.path.join(UPLOAD_FOLDER, filename))
file.save(os.path.join(UPLOAD_FOLDER, unique_filename))
print(os.path.join(UPLOAD_FOLDER, unique_filename))
# unique_thumbnail = save_thumbnail(os.path.join(UPLOAD_FOLDER, unique_filename))
# print('upload_image filename: ' + filename)
flash('Image successfully uploaded and displayed')
# if 'waybill_images' in request.url:
# # return templates.TemplateResponse('waybillData.html', {'name':waybillNo, 'filename':unique_filename, 'info':info})
# return RedirectResponse(referrer)
# else:
# return templates.TemplateResponse('upload.html', {'filename':unique_thumbnail})
# # return templates('upload.html', filename=unique_filename)
else:
flash('Allowed image types are -> png, jpg, jpeg, gif')
return RedirectResponse(referrer)
async def create_upload_file(type: str,
format: str,
background_tasks: BackgroundTasks,
model: UploadFile = File(...),
dataset: UploadFile = File(default=None)):
print("uploading", flush=True)
global labels, datapath, instanceReady
instanceReady = False
if ((format == 'edgetpu' or format == 'tflite_quantized')
and dataset == None):
return {'No representative dataset supplied'}
model_dir = tempfile.mkdtemp()
print("### Created " + model_dir)
data_dir = tempfile.mkdtemp()
unzipFile(model, model_dir)
background_tasks.add_task(cleanup_files, model_dir, data_dir)
with open(model_dir + '/metadata.json') as json_file:
data = json.load(json_file)
labels = data['labels']
print("Generating lables.txt")
with open(model_dir + '/labels.txt', 'w') as f:
for idx, label in enumerate(labels):
f.write("{} {}\n".format(idx, label))
print('Labels:' + ', '.join(labels), flush=True)
print('converting model to keras', flush=True)
os.system(
'tensorflowjs_converter --input_format tfjs_layers_model --output_format keras "'
+ model_dir + '/model.json" ' + model_dir + '/keras_model.h5')
if format == 'keras':
return returnFile('keras_model.h5', model_dir, data_dir)
# Generate savedmodel
print('converting model to saved model', flush=True)
model = tf.keras.models.load_model(model_dir + '/keras_model.h5')
model.save(model_dir + '/model.savedmodel')
if format == 'savedmodel':
return returnFile('model.savedmodel', model_dir, data_dir, True)
if format == 'tflite':
# Generate tflite unquantized
tflite_unquant_model = convertSavedModelTFLiteUnQuantized(
model_dir + '/model.savedmodel')
open(model_dir + '/model_unquant.tflite',
'wb').write(tflite_unquant_model)
return returnFile('model_unquant.tflite', model_dir, data_dir)
# Generate tflite
unzipFile(dataset, data_dir)
datapath = data_dir
print('convert model to tflite', flush=True)
tflite_quant_model = converterSavedModelTFLite(model_dir +
'/model.savedmodel')
open(model_dir + '/model.tflite', 'wb').write(tflite_quant_model)
if format == 'tflite_quantized':
return returnFile('model.tflite', model_dir, data_dir)
# Generate edgetpu model
print('compile model for edgetpu', flush=True)
os.system('edgetpu_compiler -s ' + model_dir + '/model.tflite -o ' +
model_dir)
if format == 'edgetpu':
return returnFile('model_edgetpu.tflite', model_dir, data_dir)
else:
return {'invalid format': format}