val = 0.5 - val / 2
l.append(val)
Features['FacesNumber3'] = len(l)
if Features['FacesNumber3'] > 0:
Features['AverageSex2'] = np.mean(l)
# print len(l), l
except Exception, e:
print('error SKYBIOMETRY ' + str(e), file=sys.stderr)
############################# LUKASZ.FLOWERS, BIRDS #################################
try:
file = cStringIO.StringIO(urllib.urlopen(ImURL).read())
image = Image.open(file)
Features['Classifier_Flowers_Score'] = predict_adopted.predict(
"FLOWERS", image)
Features['Classifier_Birds_Score'] = -1
except Exception, e:
print('error CLASSIFIER ' + str(e), file=sys.stderr)
############################# SAVE [ TO FILE + STDOUT ] #################################
data['content']['height'] = data4['height']
data['content']['width'] = data4['width']
data['content']['features'] = Features
output = open('data.json', 'wb')
output.write(json.dumps(data, indent=2))
output.close()
#output = open('data.json', 'rb')
#data = json.load(output)
log('error SKYBIOMETRY' + str(e))
############################# LUKASZ.FLOWERS, BIRDS #################################
data['softwareAgent_id'] = 'fr_classifier'
data['documentType'] = data['softwareAgent_id']
data['softwareAgent_label'] = 'classifier: set of classes'
data['softwareAgent_configuration'] = "flowers"
data['documentType'] = data['softwareAgent_id'] + "-" + data['softwareAgent_configuration']
data['content'] = {}
data['parents'] = [parentID]
data['content']['URL'] = ImURL
Features = {}
Features["classifier"] = []
try:
file = cStringIO.StringIO(urllib.urlopen(ImURL).read())
image = Image.open(file)
val = predict_adopted.predict("FLOWERS", image) / 100.0
Features["classifier"].append({'label' : 'flowers', 'score' : val })
data['content']['features'] = Features
th = 0.55
data['threshold'] = th
data['relevantFeatures'] = []
if val > th:
data['relevantFeatures'].append("flowers")
r = requests.post(url, data=json.dumps(data), headers=headers)
print (r)
log(r)
if WRITE_FILE==1:
output.write(json.dumps(data, indent = 2))
except Exception, e:
print('error CLASSIFIER' + str(e), file=sys.stderr)
log("error SKYBIOMETRY" + str(e))
############################# LUKASZ.FLOWERS, BIRDS #################################
data["softwareAgent_id"] = "fr_classifier"
data["documentType"] = data["softwareAgent_id"]
data["softwareAgent_label"] = "classifier: set of classes"
data["softwareAgent_configuration"] = "flowers"
data["documentType"] = data["softwareAgent_id"] + "-" + data["softwareAgent_configuration"]
data["content"] = {}
data["parents"] = [parentID]
data["content"]["URL"] = ImURL
Features = {}
Features["classifier"] = []
try:
file = cStringIO.StringIO(urllib.urlopen(ImURL).read())
image = Image.open(file)
val = predict_adopted.predict("FLOWERS", image) / 100.0
Features["classifier"].append({"label": "flowers", "score": val})
data["content"]["features"] = Features
th = 0.55
data["threshold"] = th
data["relevantFeatures"] = []
if val > th:
data["relevantFeatures"].append("flowers")
r = requests.post(url, data=json.dumps(data), headers=headers)
print(r)
log(r)
if WRITE_FILE == 1:
output.write(json.dumps(data, indent=2))
except Exception, e:
print("error CLASSIFIER" + str(e), file=sys.stderr)
l.append(val)
Features['FacesNumber3'] = len(l)
if Features['FacesNumber3'] > 0:
Features['AverageSex2'] = np.mean(l)
# print len(l), l
except Exception , e:
print('error SKYBIOMETRY '+ str(e), file=sys.stderr)
############################# LUKASZ.FLOWERS, BIRDS #################################
try:
file = cStringIO.StringIO(urllib.urlopen(ImURL).read())
image = Image.open(file)
Features['Classifier_Flowers_Score'] = predict_adopted.predict("FLOWERS", image)
Features['Classifier_Birds_Score'] = -1
except Exception , e:
print('error CLASSIFIER ' + str(e), file=sys.stderr)
############################# SAVE [ TO FILE + STDOUT ] #################################
data['content']['height'] = data4['height']
data['content']['width'] = data4['width']
data['content']['features'] = Features
output = open('data.json', 'wb')
output.write(json.dumps(data, indent = 2))
output.close()
