def write_sort_feature(self,img_features, label_center, centers):
for j, center in zip(range(len(centers)), centers):
center_dict = {}
for i, img_feature in zip(label_center, img_features):
if j == i:
feature = str(img_feature).split(",")
feature_img = feature[2:]
feature_img = list(map(float,feature_img))
dis = pdis(center, feature_img)
center_dict[img_feature] = dis
a = sorted(center_dict.items(), key=lambda x: x[1], reverse=True)
save_file = os.path.join(self.save_sort_feature_path,str(j)+".txt")
with open(save_file, 'w') as f:
for key in a:
f.write(key[0] + "," + str(float(key[1])))
f.write("\n")
def write_sort_feature(self, all_features, label_centers, centers,goods_upcs,img_file_names):
for j, center in zip(range(len(centers)), centers):
center_dict = {}
for i, img_feature,good_upc,img_file_name in zip(label_centers, all_features,goods_upcs,img_file_names):
if j == i:
dis = pdis(center, img_feature)
file_feature = str(good_upc)+","+str(img_file_name)+","
for feat in img_feature:
file_feature = file_feature+","+str(float(feat))
center_dict[file_feature] = dis
a = sorted(center_dict.items(), key=lambda x: x[1], reverse=True)
save_file = os.path.join(self.save_sort_feature_path, str(j) + ".txt")
with open(save_file, 'w') as f:
for key in a:
f.write(key[0] + "," + str(float(key[1])))
f.write("\n")
def add_good_img(self, request):
try:
img_local_file = request.POST.get('img_local_file')
goods_shelfgoods_id = request.POST.get('goods_shelfgoods_id')
good_upc = request.POST.get('good_upc')
trace_id = request.POST.get('trace_id')
log.info(
"trace_id = {%s},img_local_file={%s},goods_shelfgoods_id={%s}"
%
(str(trace_id), str(img_local_file), str(goods_shelfgoods_id)))
if os.path.isfile(img_local_file) == False:
log.error(
"trace_id = {%s},img_local_file is not exsit,img_local_file={%s},goods_shelfgoods_id={%s}"
% (str(trace_id), str(img_local_file),
str(goods_shelfgoods_id)))
return HttpResponse(str(result_failed()))
file_features = feature.get_feature_by_net(img_local_file)
featArr = file_features[0][0]
(w, h) = featArr.shape
featArr.resize(1, w * h)
featArr.resize(h, w)
print(featArr.shape)
f1s = []
for f1 in featArr:
f1s.append(float(np.sum(f1)))
cluter_label = clf.predict([f1s])[0]
to_cluter_dis = pdis(f1s, clf.cluster_centers_[cluter_label])[0]
# filename = os.path.basename(os.path.realpath(img_local_file))
# online.save_new_goods_feature(cluter_label, to_cluter_dis, good_upc, f1s, filename)
online.save_new_goods_feature(cluter_label, to_cluter_dis,
good_upc, f1s, goods_shelfgoods_id)
log.info(
"trace_id={%s},img_local_file={%s},add_good_img sucess,cluter_label={%s}"
% (str(trace_id), img_local_file, str(cluter_label)))
data = ''
return HttpResponse(str(result_success(data)))
except:
log.trace()
def euc_dist(X, Y=None, Y_norm_squared=None, squared=False):
return pdis(X, Y)