def custom_image_clf_train_controller(request):
if request.method == "POST":
pretty_request(request)
params = json.loads(request.body.decode(CHARSET))
user_id = request.META['HTTP_USER_ID']
train_request = ImageClfRequest(params)
job_id = create_job(user_id, TRAIN, train_request.service, train_request.name)
train_component.delay(params, user_id, job_id)
response = {"job_id":job_id}
return HttpResponse(json.dumps(response), content_type=CONTENT_TYPE, status=200)
def face_detection_image_controller(request):
try:
if request.method == "POST":
pretty_request(request)
with open('original_image', 'wb') as f:
f.write(request.FILES['image'].read())
image_path = "original_image"
response = face_detection_image(image_path)
return HttpResponse(response, content_type=CONTENT_TYPE, status=200)
except Exception as e:
traceback.print_exc()
return HttpResponse(e.args, status=500, content_type=CONTENT_TYPE)
def job_list(request):
try:
if request.method == "POST":
print(pretty_request(request))
user_id = request.META['HTTP_USER_ID']
params = json.loads(request.body.decode(CHARSET))
status = params['status']
service = params['service']
jobs_list = []
if status == "ALL":
jobs_list = JobStatus.objects.filter(user_id=user_id, task=constants.TRAIN, service=service).values()
elif status == constants.FINISH:
jobs_list = JobStatus.objects.filter(user_id=user_id, task_status=constants.FINISH, task=constants.TRAIN, service=service).values()
response = []
for job in jobs_list:
x = {
"status" : job["task_status"],
"output": job["output"]
}
response.append(x)
output={}
output["job_list"] = response
return HttpResponse(json.dumps(output), content_type=CONTENT_TYPE, status=200)
except Exception as e:
traceback.print_exc()
return HttpResponse(e.args, status=500, content_type=CONTENT_TYPE)
def custom_image_clf_predict_controller(request):
if request.method == "POST":
print(pretty_request(request))
params = json.loads(request.body.decode(CHARSET))
user_id = request.META['HTTP_USER_ID']
prediction_request = PredictionRequest(params)
job_id = create_job(user_id, PREDICT, prediction_request.service, prediction_request.name)
predict_component.delay(params, user_id, job_id)
response = {"job_id": job_id}
return HttpResponse(json.dumps(response), content_type=CONTENT_TYPE, status=200)
def image_clf_controller(request):
try:
if request.method == "POST":
print(pretty_request(request))
with open('clf_image.jpg', 'wb') as f:
f.write(request.FILES['image'].read())
image_path = "clf_image.jpg"
response = image_classification(image_path)
return HttpResponse(json.dumps(response), content_type=CONTENT_TYPE, status=200)
except Exception as e:
traceback.print_exc()
return HttpResponse(e.args, status=500, content_type=CONTENT_TYPE)
def custom_image_clf_predict_image_controller(request):
try:
if request.method == "POST":
print(pretty_request(request))
with open('clf_image.jpg', 'wb') as f:
f.write(request.FILES['image'].read())
image_path = "clf_image.jpg"
model_url = request.POST["modelUrl"]
user_id = request.META['HTTP_USER_ID']
response = prediction_image(image_path, model_url, user_id)
return HttpResponse(json.dumps(response), content_type=CONTENT_TYPE, status=200)
except Exception as e:
traceback.print_exc()
return HttpResponse(e.args, status=500, content_type=CONTENT_TYPE)
def obj_json(request):
try:
if request.method == "POST":
print(pretty_request(request))
with open('original_image.png', 'wb') as f:
f.write(request.FILES['image'].read())
image_path = "original_image.png"
response = object_detection_json(image_path)
return HttpResponse(json.dumps(response),
content_type=CONTENT_TYPE,
status=200)
except Exception as e:
traceback.print_exc()
return HttpResponse(e.args, status=500, content_type=CONTENT_TYPE)
def license_plate_image_controller(request):
try:
if request.method == "POST":
print(pretty_request(request))
with open('lp.png', 'wb') as f:
f.write(request.FILES['image'].read())
image_path = "lp.png"
response = licence_plate_image(image_path)
return HttpResponse(response,
content_type=CONTENT_TYPE,
status=200)
except Exception as e:
traceback.print_exc()
return HttpResponse(e.args, status=500, content_type=CONTENT_TYPE)
def custom_obj_detection_predict_image_controller(request):
try:
if request.method == "POST":
print(pretty_request(request))
with open('original_image.png', 'wb') as f:
f.write(request.FILES['image'].read())
image_path = "original_image.png"
model_url = request.POST["modelUrl"]
user_id = request.META['HTTP_USER_ID']
response = custom_object_detection_image(model_url, image_path,
user_id)
return HttpResponse(response,
content_type=CONTENT_TYPE,
status=200)
except Exception as e:
traceback.print_exc()
return HttpResponse(e.args, status=500, content_type=CONTENT_TYPE)
def job_status(request, job_id):
try:
if request.method == "GET":
print(pretty_request(request))
job = JobStatus.objects.get(job_id=job_id)
response = {
"task": job.task,
"status" : job.task_status,
"output": job.output
}
if response is not None:
return HttpResponse(json.dumps(response), content_type=CONTENT_TYPE, status=200)
else:
raise JobNotFoundError()
except Exception as e:
traceback.print_exc()
return HttpResponse(e.args, status=500, content_type=CONTENT_TYPE)
