changbaishan

Results 10 issues of changbaishan

#### Issue Description Please describe your issue, along with: - expected behavior: work - encountered behavior: Exception111 : File missing for any of the specified labels Cause: A bug in...

bug

The example for "Remove Distortion" is quite beautiful. The reverse is to place an image into a specified area of an image, most likely distorted. I wonder if it can...

Example Request

RuntimeError Traceback (most recent call last) in 9 models = dict() 10 for key,fun in six.iteritems(model_inits): ---> 11 net = fun(n_classes, pretrained=True).eval() 12 if has_cuda: 13 net = net.cuda() ~/Documents/sandbox/torch/light-weight-refinenet/models/resnet.py...

bug

Segmented image can be displayed with vis_semantic_segmentation function. It can be saved as a result. What I suggest is a separate function that can return the segmented image directly. This...

feature request

My user gives me a feedback that markers on the map block the city names on the map. They also like your markers, they are informative. Would it be possible...

leaflet-openweathermap has an option of switching temperature unit. When I set the temperature unit to F. Everything in map changed accordingly. However, the image that indicate temperature scale remains unchanged....

(1) python style_transfer.py --train ../data/yelp/sentiment.train --dev ../data/yelp/sentiment.dev --output ../tmp/sentiment.dev --vocab ../tmp/yelp.vocab --model ../tmp/model File "style_transfer.py", line 194 print 'Loading model from', args.model ^ SyntaxError: Missing parentheses in call to 'print'...

training = prepare_data(training) validation = prepare_data(validation) test = prepare_data(test) print('Build model...') print('Vocab size =', VOCAB) AttributeError Traceback (most recent call last) in ----> 1 training = prepare_data(training) 2 validation =...

We know it is old code. However, people at twitter are using and recommending codes that depend on it. So the broken annotation should be fixed so that at least...

# Load the trained file from the module root. trained_file = data.lbp_frontal_face_cascade_filename() the data object no longer contains lbp_frontal_face_cascade_filename() # Initialize the detector cascade. detector = Cascade(trained_file) skimage.feature no longer...