bnn | bee detection tensorflow conv net for a rasp pi | Computer Vision library
kandi X-RAY | bnn Summary
kandi X-RAY | bnn Summary
unet style image translation from image of hive entrance to bitmap of location of center of bees. trained in a semi supervised way on a desktop gpu and deployed to run in real time on the hive using either a raspberry pi using a neural compute stick or a je vois embedded smart camera. see this blog post for more info.. here's an example of predicting bee position on some held out data. the majority of examples trained had ~10 bees per image. the ability to locate each bee means you can summarise with a count. note the spike around 4pm when the bees at this time of year come back to base.
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Top functions reviewed by kandi - BETA
- Create a debug image
- Calculate the centroids of all connected components
- Convert a bitmap to a PIL Image
- Convert an array to a PIL image
- Convert a list of images into a PIL image
- Generate a bitmap from a list of centroids
- Convert bitmap to a single channel image
- Restore model from checkpoint
- Construct a convolutional model
- Display next image
- Display previous image
- Convert a list of images to a bitmap
- Generator for training images
- Compiles the model
- Returns the precision recall function
- Redraw a red rectangle
- Convert a bitmap to a single channel image
- Display the next un labeled image
- Constructs a convolutional model
- Convert PIL image to a tf Summary
- Convert seconds to hours minutes
- Remove the closest bee event
- Toggle bees
- Create db if necessary
- Copy a bitmap to the right side of the image
- Compute the distance between two sets
bnn Key Features
bnn Examples and Code Snippets
Lines of Code : 70License : Permissive (MIT License)
Copydef reverse_bwt(bwt_string: str, idx_original_string: int) -> str:
"""
:param bwt_string: The string returned from bwt algorithm execution
:param idx_original_string: A 0-based index of the string that was used to
generate bwt_stri def bwt_transform(s: str) -> BWTTransformDict:
"""
:param s: The string that will be used at bwt algorithm
:return: the string composed of the last char of each row of the ordered
rotations and the index of the original string at o Community Discussions
Trending Discussions on bnn
QUESTION
There are two string sequences: 1 - main string: regardless of the length, it can be divided to sets of complete triplets. This sequence comes with a dictionary containing keys that are different triplets and values that are number represented as string. Triplets with the same value are alternatives of each other.
...ANSWER
Answered 2021-Oct-12 at 10:18I figured it on my own!
1 - Make triplet sets of the main sequence
2 - Detect to which set the user_input aligns with
3 - Find the alternatives for those sets in the dictionary
4 - add the new sets to the list and remove the old ones
5 - join the sets to reconstruct the new main sequence
QUESTION
Trying to create reports using PowerBI, where I can easily upload JSON file and populate the data without any problem. Since Im new to powerBI, I'm not able get proper information for my issue.
Below is my sample JSON data. I want to show the different status counts in card view, (i.e) need to show total number of customer, Active, InActive, Suspended etc
...ANSWER
Answered 2021-Jun-23 at 10:03here:
QUESTION
Number of possible combinations for the given Indices
for example the indice[0] of the word BANANA
should give me :
ANSWER
Answered 2021-Jun-20 at 12:15You can create the combinations, based on index on a given word, forward way.
QUESTION
I am trying to implement a binary classification with Neural Networks with Pytorch to train a model as shown below:
...ANSWER
Answered 2021-Apr-13 at 00:28I'll attempt to answer your questions:
Question 1 & 2:
Is it a right way to train a model? In many articles I found that there is a section to iterate over the DataLoader for training data.
You should use a dataset with a dataloader when training in pytorch for several reasons:
- It allows us to sample our data randomly
- It doesn't preload data into memory, which is particularly useful for huge datasets
- It operates in the background of code so fetches data parallel to training, thus saving time
- It's very efficient at batching your data
What you're doing here is seemingly running your model on every element in your data at once. If you only have 32 points in your data this might be fine (although really not optimal because you have such limited data) but there is a balance to strike between running your optimizer and exposing your model to learning opportunities.
I would guess this takes longer because your model is very small and it probably takes longer to run the data fetching than it does when it's already preloaded in memory. It is hard to answer this without knowing the size of your dataset and the batch size of your processing.
Question 3: Is it right way to test the model that I trained above?
You need to set your model to its evaluation stage using model.eval() before you run any inference code. I also don't understand the point of your for loop since you just pass through the same data every time. I would generally run something like this:
QUESTION
I've got some constants defined like this
...ANSWER
Answered 2020-Nov-28 at 09:37- Use Symbols instead of constants.
- Don't expose the mapping.
Constants in Ruby are mostly about information hiding. For example, if the key changes from consumer1 to consumer_1 as long as everything accesses the Hash with CONSUMER_1_TYPE you're ok. Why risk it?
Instead, fully hide the Hash. Now that it's hidden, constants are not necessary. Use Symbols.
If all the values are going to be the same, put them into their own methods.
QUESTION
Let's say I got these strings:
P 1 (BNN-03) Voertuig te water Curacaostraat Groningen 011810 011871 013593 011833
A1 AMBU 18177 Binnendams 3373AE Hardinxveld-Giessendam HARDGD bon 81505
Prio 4(DIA: ja) AMBU 17104 F. Bordewijkstraat 3069WB Rotterdam ROTTDM bon 29230
I've written the following regex to test on them:
...ANSWER
Answered 2020-Jul-05 at 20:10You can use slices, change:
QUESTION
I'm learning Python3 and I'm trying to create an object Agent (a custom object) by initiating the attributes of it from a JSON file.
The problem is that when I launch my python file, it does not find the file, which is in the same directory. I checked the name and the is no typo. I don't understand where the problem really is.
Here is my folder structure:
...ANSWER
Answered 2020-Mar-30 at 13:31Python opens the file relative to where the script is executed. So if you run the file with project/model.py the json should be outside of the project folder.
If the json is always included on the same folder that your python file you can use the follow code to open the file:
QUESTION
I'm sort of new to iOS development using Swift. So, I might be missing a simple solution in Swift that I'm not aware of. I am working on a tvOS app where I display a list of video content that the user can select from. The app also contains a settings tab that allows the user to configure 5 different types of settings. Once they select a specific category, it displays a new table view with the corresponding options which are in the options array. This is where the "issue" is that I need help.
I have this struct which I'm using as a singleton:
...ANSWER
Answered 2020-Feb-18 at 18:11First of all create an enum Category,
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Install bnn
You can use bnn like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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