def notifications(self, from_date=None, to_date=None):
if not to_date:
to_date = date2str(datetime.utcnow())
from_date = date2str(datetime.utcnow() - timedelta(days=7))
poll_url = self.baseURL + "/SentNotifications/" + self.token + \
"?from=" + from_date + "&to=" + to_date
print(poll_url)
response = requests.get(poll_url)
data = response.json().get("Result")
print(len(data), json.dumps(data, indent=4))
return data
def sensor_data(self, sensor_id, from_date=None, to_date=None):
if not to_date:
to_date = date2str(datetime.utcnow())
from_date = date2str(datetime.utcnow() - timedelta(days=7))
poll_url = self.baseURL + "/SensorDataMessages/" + self.token + "?" +\
"sensorID=" + str(sensor_id) + "&fromDate=" + from_date + \
"&toDate=" + to_date
response = requests.get(poll_url)
data = None
print(response.status_code, response.reason)
if response.status_code == 200:
data = response.json().get("Result")
print(json.dumps(data, indent=4))
return data
def save_segments(original_image, segments, image_saved_path):
original_image = original_image.split(".")[0]
output_names = []
time = date2str()
for k, segment in enumerate(segments):
pil_object = Image.fromarray(segment.astype('uint8'), 'RGB')
output_name = original_image + "segment{0}_{1}.jpg".format(k, time)
output_names.append(output_name)
pil_object.save(image_saved_path + output_name)
return output_names
def _async_select(self, sql, vals, inst=None, **kwargs):
ret = []
max_id = 0
key_set = set()
auto_convert = False
account_max_id = False
mk_timestamp = False
set_key = None
if kwargs.has_key("auto_convert"):
auto_convert = kwargs["auto_convert"]
if kwargs.has_key("account_max_id"):
account_max_id = kwargs["account_max_id"]
if kwargs.has_key("mk_timestamp"):
mk_timestamp = kwargs["mk_timestamp"]
if kwargs.has_key("set_key"):
set_key = kwargs["set_key"]
if not vals:
vals = None
if not inst:
inst = self.get_mysql_inst(**kwargs)
cursor = yield inst.execute(sql, vals)
for row in cursor:
tmp = {}
for i in range(0, len(row)):
colval = row[i]
if auto_convert:
if isinstance(colval, datetime.date) or isinstance(
colval, datetime.datetime):
if mk_timestamp:
colval = utils.date2int(colval)
else:
colval = utils.date2str(colval)
elif isinstance(colval, float):
colval = str(colval)
tmp[cursor.description[i][0]] = colval
if account_max_id and cursor.description[i][
0] == "id" and colval > max_id:
max_id = colval
if set_key and cursor.description[i][0] == set_key:
key_set.add(colval)
ret.append(tmp)
tmp_ret = [ret]
if account_max_id:
tmp_ret.append(max_id)
if set_key:
tmp_ret.append(key_set)
if len(tmp_ret) > 1:
raise gen.Return(tuple(tmp_ret))
else:
raise gen.Return(tmp_ret[0])
def save_masks(original_image, masks, image_saved_path):
original_image = original_image.split(".")[0]
output_names = []
time = date2str()
for k, mask in enumerate(masks):
def img_frombytes(data):
size = data.shape[::-1]
databytes = np.packbits(data, axis=1)
return Image.frombytes(mode='1', size=size, data=databytes)
pil_object = img_frombytes(mask)
output_name = original_image + "mask{0}_{1}.jpg".format(k, time)
output_names.append(output_name)
pil_object.save(image_saved_path + output_name)
return output_names
def train(model, epochs, train_loader, val_loader=None, frequency=5):
config = get_light_mask_rcnn_config()
learning_rate = config['learning_rate']
decay_param = config['decay_param']
num_warmup_steps = config['num_warmup_steps']
checkpoint_path = config['checkpoints']
optimizer = AdamW(model.parameters(), lr=learning_rate, eps=1e-8)
num_training_steps = len(train_loader) * epochs
scheduler = get_linear_schedule_with_warmup(
optimizer,
num_warmup_steps=num_warmup_steps,
num_training_steps=num_training_steps)
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
#device = torch.device("cpu")
model.to(device)
record = []
for epoch in range(epochs):
timestamp = date2str()
metric_logger = train_one_epoch(model, optimizer, scheduler,
train_loader, device, epoch, frequency,
num_warmup_steps, True)
record.append(metric_logger)
if val_loader is not None:
coco_evaluator = evaluate(model, val_loader, device)
file_name = checkpoint_path + 'coco_evaluator_{0}.pkl'.format(
timestamp)
with open(file_name.format(timestamp), 'wb') as f:
pickle.dump(coco_evaluator, f)
if epoch % frequency == 0:
save_checkpoint(
{
'epoch': epoch,
'state_dict': model.state_dict(),
'optimizer': optimizer.state_dict(),
'scheduler': scheduler.state_dict(),
},
checkpoint_path,
timestamp=timestamp)
file_name = checkpoint_path + 'loss_{0}.pkl'.format(timestamp)
with open(file_name.format(timestamp), 'wb') as f:
pickle.dump(record, f)
file_name = checkpoint_path + "resnet_101.pth"
torch.save(model.state_dict(), file_name)
table = HtmlTable(border=1, cellpadding=3)
# table header
header = ['#',
'<a href= "main2.py?order_by=title">Title</a>',
'<a href= "main2.py?order_by=author">Author</a>',
'<a href= "main2.py?order_by=notes">Notes</a>',
'<a href= "main2.py?order_by=when_read">Date</a>']
table.addHeader(header)
# table body
i = 0
for (book_id, title, author, notes, when_read) in results:
i += 1
href = '<a href="detail.py?book_id=%d">%s' % (book_id, title)
date = '<nobr>%s</nobr>' % date2str(when_read)
table.addRow([i, href, author, notes, date])
# Output HTML
print 'Content-Type: text/html\n'
print "<html>"
print """
<head>
<title> Read A Book! </title>
<link href="css/main.css" rel="stylesheet" type="text/css">
</head>"""
print "<body>"
print "<h3>Books, Authors, and Notes</h3>"
if value == None:
value= 'Unknown'
#Special Handeling for binary field published
if key =='published':
key = 'Published'
if key == 'Published' and value == 1:
value = 'Yes'
if key == 'Published' and value == 0:
value = 'No'
#Special handeling for date output
if key == 'when_read':
key= 'Date Read'
value =date2str(value)
# form +='''<br>
# %s: <input type = "textfield" name = "entry" value = "%s"><br>
# '''% (key, value)
if key == 'title':
key = 'Title'
form += '''<br>
%s: <input type = "textfield" name = "entry" value = "%s"><br>
'''% (key, value)
if key == 'last_name':
key = 'Author Last Name'
form += '''<br>
%s: <input type = "textfield" name = "entry" value = "%s">
def __doc_acu(request, id, mode):
'''
Anon/Create/Update
:param id:int - uuid (anon/create) or doc id (update)
:param mode:int (0: anon (print), 1: create, 2: update)
'''
__log_request(request)
if (mode == 2):
item = models.Doc.objects.get(pk=id) # Update only
uuid = item.type
if (uuid not in moduledict):
return 'Template not found'
else:
uuid = id
if (request.method == 'POST') and (mode > 0) and (request.POST.get('_action', None) in set(('print', 'view'))):
mode = 0
tpl = moduledict[uuid]
# 1. check <pkg>.ANON/CREATE/UPDATE
self_func = [K_T_F_ANON, K_T_F_ADD, K_T_F_EDIT][mode]
if (self_func in tpl[K_V_MODULE].__dict__):
return tpl[K_V_MODULE].__dict__[self_func](request, id)
# else:
# 2. get FORM and FORMSETS
formclass = tpl[K_T_FORM]
formsetsclass = tpl[K_T_FORMSETS] # SortedDict of dicts
if request.method == 'POST':
#pprint.pprint(request.POST['_action'])
form = formclass(request.POST)
if (mode == 0): # ANON, Create/Update -> view/print
del form.fields[K_T_F_NAME]
formlist = SortedDict()
isvalid = form.is_valid()
for k, formset in formsetsclass.iteritems():
formlist[k] = formset(request.POST, prefix=k)
isvalid = isvalid and formlist[k].is_valid()
if isvalid:
data = form.cleaned_data
# inject formsets into data
for k, v in formlist.iteritems():
dataset = list()
for i in v.cleaned_data: # list of dicts
if i: # reject empty dicts
dataset.append(i)
if dataset: # reject empty lists
data[k] = dataset # inject datasets into data
__try_to_call(tpl, K_T_F_POST_FORM, data)
# split
if (mode == 0): # ANON > PRINT, C/U -> V/P
if ((K_T_T in tpl[K_V_MODULE].DATA) and (K_T_T_PRINT in tpl[K_V_MODULE].DATA[K_T_T])):
context_dict = {'data': data}
template = tpl[K_V_MODULE].DATA[K_T_T][K_T_T_PRINT]
if (request.POST.get('_action', None) == u'view'):
__try_to_call(tpl, K_T_F_PRE_VIEW, data) # Create/Update -> View
return converter.html2html(request, context_dict, template)
else: # Anon/Create/Update -> PRINT
__try_to_call(tpl, K_T_F_PRE_PRINT, data)
return __doc_print(request, context_dict, template)
else: # tmp dummy
return redirect('dox.views.index')
else: # CREATE/UPDATE -> SAVE
if (mode == 1): # CREATE
name = data[K_T_F_NAME]
else:
item.name = data[K_T_F_NAME]
del data[K_T_F_NAME]
# convert dates
if (K_V_DATES in tpl):
for k in tpl[K_V_DATES]:
utils.date2str(data, k)
__try_to_call(tpl, K_T_F_PRE_SAVE, data)
if (mode == 1): # CREATE
# user, type, name, data
item = models.Doc(user=request.user, type=uuid, name=name, data=json.dumps(data, indent=1, ensure_ascii=False))
else:
item.data = json.dumps(data, indent=1, ensure_ascii=False)
item.save()
return redirect(doc_r, id=item.pk)
else: # GET
if (mode < 2): # ANON, CREATE
form = formclass()
if (mode == 0): # ANON
del form.fields[K_T_F_NAME]
formlist = SortedDict()
for k, formset in formsetsclass.iteritems():
formlist[k] = formset(prefix=k)
else: # UPDATE
data = json.loads(item.data)
data[K_T_F_NAME] = item.name # inject name
# restore dates after loading
if (K_V_DATES in tpl):
for k in tpl[K_V_DATES]:
utils.str2date(data, k)
#pprint.pprint(data)
__try_to_call(tpl, K_T_F_POST_LOAD, data)
#pprint.pprint(data)
__try_to_call(tpl, K_T_F_PRE_FORM, data)
# split form and formsets
# 1. eject formsets
formlist = SortedDict([])
for pfx, formset in formsetsclass.iteritems(): # formsetsclass == SortedDict {name: FormSetClass}
formset_data = dict()
for i, l in enumerate(data.get(pfx, list())): # l:str - formset name; l:
for k, v in l.iteritems():
formset_data[pfx+'-'+str(i)+'-'+k] = v
formset_data.update({
pfx+'-TOTAL_FORMS': len(data[pfx]) if pfx in data else 1,
pfx+'-INITIAL_FORMS': u'0',
pfx+'-MAX_NUM_FORMS': u'',
})
formlist[pfx] = formset(formset_data, prefix=pfx)
if (pfx in data):
del data[pfx]
# 2. else
form = formclass(data)
return render_to_response(
tpl[K_V_MODULE].DATA[K_T_T][K_T_T_FORM] if ((K_T_T in tpl[K_V_MODULE].DATA) and (K_T_T_FORM in tpl[K_V_MODULE].DATA[K_T_T])) else 'auto_form.html',
context_instance=RequestContext(request, {
'name': tpl[K_V_MODULE].DATA[K_T_NAME],
'comments': tpl[K_V_MODULE].DATA[K_T_COMMENTS],
'legend': tpl[K_V_MODULE].DATA.get(K_T_LEGEND, ''),
'uuid': tpl[K_V_MODULE].DATA[K_T_UUID],
'form': form,
'formlist': formlist,
'example': tpl[K_V_MODULE].DATA.get('example', None),
}))