Coco | The fastest crypto online | Blockchain library
kandi X-RAY | Coco Summary
kandi X-RAY | Coco Summary
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Top functions reviewed by kandi - BETA
- Validate transaction
- Generate a random hash for a blob
- Compare two byte arrays
- Validate the share date
- Creates the transaction
- Applies a value to the prepared statement
- Insert values into the table
- Main method
- Computes the hash of the blob
- Initialize the panel
- The main application
- Main entry point
- Initializes the FXML component
- Queries the block hash
- Loads the popup
- Enter a transaction
- Starts a new work
- Load a block of image
- Retrieves the balance
- On add transaction
- Handle the continue password
- Fetch a sender
- Handle the handler
- Sign the request
- Handle the request
- Executes the request
Coco Key Features
Coco Examples and Code Snippets
Lines of Code : 99License : Non-SPDX (Apache License 2.0)
Copydef _get_ground_truth_detections(instances_file,
allowlist_file=None,
num_images=None):
"""Processes the annotations JSON file and returns ground truth data corresponding to allowlis def load_class_names(namesfile):
# Create an empty list to hold the object classes
class_names = []
# Open the file containing the COCO object classes in read-only mode
with open(namesfile, 'r') as fp:
# The Community Discussions
Trending Discussions on Coco
QUESTION
I want to detect more objects than coco dataset which detects only 80 objects , I want to detect as many as possible actions also like hugging ,swimming.....etc.
I don't care about the size and I do not want to train myself ... So is there a dataset(weights) big enough already available that I can download and use or I do have to train and label for yolo?
...ANSWER
Answered 2021-Jun-13 at 13:54What you are trying to classify is represented as Action Recognition. Here [1] is a good repo that lists a lot of out-of-the-box models for this task.
An explanation: Models (like YOLO) contain two main blocks: feature extraction (CNN stuff) and classification (linear layers). When training from scratch, both feature extraction and classification will be trained from scratch. It is easy to train classification to what you want, but it is hard to train the feature extraction part (as it takes a lot of time). Hence, we typically use pre-trained models on generalized datasets (like YOLO is trained on COCO), so our feature extraction part starts from a somewhat good generalized place. Later, we replace the classification part will our own to be trained from scratch for our task.
TL;DR, you can use a pre-trained YOLO model on COCO for your task by replacing the last linear layers to classify what you want. Here are some resources for different frameworks [2, 3].
Here [4] is a simple walkthrough of how to do this.
- [1] https://github.com/jinwchoi/awesome-action-recognition/blob/master/README.md#action-recognition-and-video-understanding
- [2] TensorFlow: https://www.tensorflow.org/tutorials/images/transfer_learning
- [3] PyTorch: https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html
- [4] https://blog.roboflow.com/training-yolov4-on-a-custom-dataset/
QUESTION
I am attempting to download a file from a web server using the standard TIdHTTP and TIdSSLIOHandler components in Delphi 10.4:
ANSWER
Answered 2021-Jun-13 at 19:01Instead of loading the resource to memory temporarily, directly load it to the local file using a TFileStream:
QUESTION
Describe the problem
To read a model from official TensorFlow source (COCO SSD MobileNet v1) and perform inference with minimal.cc, we get the error below.
System information
- Host OS Platform and Distribution : Linux Ubuntu 16.04
- TensorFlow installed from (source or binary): From source (branch r1.12)
- Target platform: iMX.6 (Arm v7)
Please provide the exact sequence of commands/steps when you ran into the problem
...ANSWER
Answered 2021-May-24 at 01:57Looks like the TensorFlow Lite version is too old to be supported. Please consider using TF 2.5 or beyonds.
QUESTION
I would like the last field to have 50px border radius on the right. Why is this not working?
...ANSWER
Answered 2021-Jun-07 at 09:07Add this css on your code
QUESTION
I'm trying to add a new function to an existing class Node defined inside the namespace cc. The namespace is declared as follows:
creator.d.ts
...ANSWER
Answered 2021-Jun-04 at 12:00You can add a function to a class inside a namespace by first creating an interface (Node) that is wrapped inside a namespace with the same name (cc) that is then wrapped inside a declare global statement and then by adding the interface method (getWorldPosition) to the .prototype property of the type you want to extend (cc.Node).
QUESTION
I have a username and a password, I need to check both of these against the data in the JSON file, if both are correct/exist I return a list that contains the data in "items".
For example: if I type "user" for the username and "pass" for the password the view should display "Dog, Cat, Mouse, Parrot, Goldfish" in a list.
The JSON file can be modified if my syntax is incorrect.
JSON:
...ANSWER
Answered 2021-Jun-03 at 17:56You can use first(where:) to find an item in your array that matches a given condition (in this case, that the user names match). It returns an optional since there's no guarantee that there will be an item that matches.
I had to stub out UserModel and UserModelData since you didn't include them, so you'll need to make sure the type names match what you had.
QUESTION
This program is detecting the things from web cam but it's slow so how can i make it fast for better FPS and how can i use GPU for the faster detection and with better performance. And i how can i make it perfect .In this Program i have used the Yolo configuration and weights with coco dataset .
...ANSWER
Answered 2021-May-31 at 11:45To use Gpu we have to compile opencv and this can be done as follows in blog : https://haroonshakeel.medium.com/build-opencv-4-4-0-with-cuda-gpu-support-on-windows-10-without-tears-aa85d470bcd0
and after doing it add the two lines that will that will detect the Gpu and program will run on GPU.
QUESTION
I have a JSON file that contains several images and annotations. Each image has an id, and each annotation references a caption and the image_id of the image. There are thousands of images and multiple annotations refer to the same image. Here's a sample for only one image and its annotations (link to full data):
ANSWER
Answered 2021-May-29 at 07:08After reading in the data, reorganizing into an dictionary indexed by ID will make it easy to access the correct image when iterating the annotations. Below does this, but also adds each caption to a list of captions added to each image:
QUESTION
I'm looking for something that can help me with detection of eye via YOLO method. Is it even possible? Saw that COCO and pascal VOC datasets are wide but there's lack of eye class. Is there any dataset or something that could help me with such detection?
...ANSWER
Answered 2021-May-24 at 15:51You can manually train for custom classes. If you have GPU you can use or else use Google Colab. Here is the link for tutorial
QUESTION
I would like to train the detectron2 model with registering multiple datasets
I have extracted my annotations from the different tasks and now I have multiple datasets which we need to be trained together.
...ANSWER
Answered 2021-May-19 at 11:08Answering my own question, Apparently, there is no such method to try the multiple datasets. If you like to combine different datasets then use the COCO Assitant library. Simple step to install is !pip install coco-assistant
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Coco
You can use Coco like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Coco component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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