iNaturalist | MXNet finetune baseline for iNaturalist Challenge | Machine Learning library
kandi X-RAY | iNaturalist Summary
kandi X-RAY | iNaturalist Summary
MXNet fine-tune baseline script (resnet 152 layers) for iNaturalist Challenge at FGVC 2017, public LB score 0.117 from a single 21st epoch submission without ensemble.
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Top functions reviewed by kandi - BETA
- Fit the model
- Get the learning rate scheduler
- Load model
- Save the model
- Download a model
- Download a file from url
- Generate a list of train images
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Trending Discussions on iNaturalist
QUESTION
I am new to Stackflow so I apologize in advance if my question isn't completely clear.
I am using R.
So I have 2 data frames.. one is Census Bureau data containing all counties in the United States and if they are classified as rural or urban. In my other dataframe, I have iNaturalist occurrence data of a moth species and I have counties and states for those occurrences.
I want to mutate a new column in the iNaturalist dataframe classifying each county and state as urban or rural using the Census Bureau data. However, I don't know how to narrow down the county data or link it to urban/rural like it is in the Census Bureau data. I'm just not sure how to achieve it through code. I've included code for heads of both dataframes. Thanks in advance for the help!
...ANSWER
Answered 2021-Jan-28 at 19:33I feel like this won't work here is what I tried to solve your problem. The problem is that there are likely duplicated county names in different states. I tried to solve that problem but it is hard to tell if what I did will work without having access to the full datasets. There is also a high likelihood that county names are structured differently between the two data sets, for example, st clair could be written as st. clair or saint clair in the census bureau dataset. If the datasets are publically available I would be happy to take a look
QUESTION
I am loading tfhub.dev model from GCS in colab TPU instance using
os.environ["TFHUB_CACHE_DIR"] = "gs://BUCKETNAME/model-cache-dir/"
ANSWER
Answered 2020-Oct-23 at 08:01This might be due to latency of copying files from GCS to GCS through the machine where colab is running.
There is a way of using default /tmp location for TFHUB_CACHE_DIR that might be faster. Try not explicitly setting TFHUB_CACHED_DIR, and instead pass LoadOptions to hub.KerasLayer with experimental_io_device='/job:localhost', e.g.
load_options = tf.saved_model.LoadOptions(experimental_io_device='/job:localhost') layer = hub.KerasLayer(..., load_options=load_options)
QUESTION
I have no experience coding!
I am having trouble scraping data from a website into my Google spreadsheet. I want to get the Observation number into my spreadsheet form this page
I have tried this but honestly have no idea what I'm doing:
...ANSWER
Answered 2020-Sep-02 at 16:20Good attempt! However, unfortunately the obvervation number is not determined until after the page loads. That means that your formula:
QUESTION
As you can see from my code I am still learning so any constructive criticism unrelated to this problem regarding my code and its structure is not only welcomed as it is greatly appreciated.
I've added coloured borders to better understand the limits of each element.
At current the problem is that the image (blue border) ought to stay inside its parent meaning the header (pink border) since I've given the image a max width of 100%. But instead 100% seems to be a specific location outside all the elements.
HTML:
...ANSWER
Answered 2020-Jan-07 at 23:07You've told your image that it's max width should be 100%, which is great, but it doesn't know the size of it's parent container. Relative size properties such as max-width must know what they are relative to, so try giving your img-div container a width dimension, for example:
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