Caranx | Large scale social image | Machine Learning library
kandi X-RAY | Caranx Summary
kandi X-RAY | Caranx Summary
Caranx is a Python library typically used in Artificial Intelligence, Machine Learning applications. Caranx has no bugs, it has no vulnerabilities and it has low support. However Caranx build file is not available. You can download it from GitHub.
`26th ACM/IEEE Supercomputing 2013` Yusheng Xie, Zhuoyuan Chen, Ankit Agrawal, Wei-keng Liao and Alok Choudhary. Caranx: Scalable Social Image Index Using Phylogenetic Tree of Hashtags. Most existing image indexing techniques rely on Scale Invariant Feature Transformation (SIFT) for extracting local point features. Applied to individual image, SIFT extracts hundreds of numerical vectors. The vectors are quantized and stored in tree-like data structures for fast search. SIFT-based indexing can exhibit weakness under certain non-rigid transformations, which are common among real world applications. For example, SIFT often cannot recognize a face as the same with different expressions (e.g. giggling vs. crying). Non-Rigid Dense Correspondence (NRDC) addresses such drawbacks of SIFT. However, directly using NRDC incurs an impractical amount of computation in large-scale image indexing. We present a novel idea here that uses social hashtags to organize the images into a phylogenetic tree (PT). We provide an efficient algorithm to build/search the PT, and show that using PT structure can effectively avoid unnecessary NRDC computation. The resulting image index provides more accurate and diversified search results.
`26th ACM/IEEE Supercomputing 2013` Yusheng Xie, Zhuoyuan Chen, Ankit Agrawal, Wei-keng Liao and Alok Choudhary. Caranx: Scalable Social Image Index Using Phylogenetic Tree of Hashtags. Most existing image indexing techniques rely on Scale Invariant Feature Transformation (SIFT) for extracting local point features. Applied to individual image, SIFT extracts hundreds of numerical vectors. The vectors are quantized and stored in tree-like data structures for fast search. SIFT-based indexing can exhibit weakness under certain non-rigid transformations, which are common among real world applications. For example, SIFT often cannot recognize a face as the same with different expressions (e.g. giggling vs. crying). Non-Rigid Dense Correspondence (NRDC) addresses such drawbacks of SIFT. However, directly using NRDC incurs an impractical amount of computation in large-scale image indexing. We present a novel idea here that uses social hashtags to organize the images into a phylogenetic tree (PT). We provide an efficient algorithm to build/search the PT, and show that using PT structure can effectively avoid unnecessary NRDC computation. The resulting image index provides more accurate and diversified search results.
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Support
Caranx has a low active ecosystem.
It has 7 star(s) with 1 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
Caranx has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Caranx is current.
Quality
Caranx has no bugs reported.
Security
Caranx has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
Caranx does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
Reuse
Caranx releases are not available. You will need to build from source code and install.
Caranx has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed Caranx and discovered the below as its top functions. This is intended to give you an instant insight into Caranx implemented functionality, and help decide if they suit your requirements.
- get image
- check for null image
- returns the url of the media table
Get all kandi verified functions for this library.
Caranx Key Features
No Key Features are available at this moment for Caranx.
Caranx Examples and Code Snippets
No Code Snippets are available at this moment for Caranx.
Community Discussions
Trending Discussions on Caranx
QUESTION
Run t.test through a list of tibbles
Asked 2020-Sep-01 at 00:19
structure(list(Species = structure(c(2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Caranxpapuensis","Caranxsexfasciatus", "Epinephelus merra", "Epinephelus polyphekadion", "Hipposcaruslongiceps", "Lethrinus nebulosus", "Lethrinus obsoletus", "Lethrinus olivaceus", "Lethrinusxanthochilus", "Lutjanus bohar", "Lutjanus fulvus", "Lutjanus gibbus", "Lutjanus kasmira", "Myripristis adusta", "Myripristis berndti", "Naso lituratus", "Naso unicornis", "Parupeneus barberinus", "Sargocentron spiniferum", "Siganus argenteus", "Sphyraena forsteri"), class = "factor"), Country = structure(c(2L, 2L, 2L, 2L, 2L, 2L), .Label = c("American Samoa", "Federated States of Micronesia", "Kiribati", "Marshall Islands", "NC"), class = "factor"), Kn = c(1.09219153997845, 0.79017036273396, 1.02547034006866, 1.11244965699788, 0.972280456514503, 0.971061586363312)), row.names = c(NA, -6L), groups = structure(list(
Species = structure(2L, .Label = c("Caranx papuensis", "Caranx sexfasciatus",
"Epinephelus merra", "Epinephelus polyphekadion", "Hipposcarus longiceps",
"Lethrinus nebulosus", "Lethrinus obsoletus", "Lethrinus olivaceus",
"Lethrinus xanthochilus", "Lutjanus bohar", "Lutjanus fulvus",
"Lutjanus gibbus", "Lutjanus kasmira", "Myripristis adusta",
"Myripristis berndti", "Naso lituratus", "Naso unicornis",
"Parupeneus barberinus", "Sargocentron spiniferum", "Siganus argenteus",
"Sphyraena forsteri"), class = "factor"), .rows = structure(list(
1:6), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = 1L, class = c("tbl_df", "tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", "tbl_df", "tbl", "data.frame"))
ANSWER
Answered 2020-Sep-01 at 00:19I think you have an incorrect syntax. Try something like this :
QUESTION
How to conditionally merge two rows with multiple values together and mutate in R?
Asked 2020-Apr-30 at 09:58
Fish have been caught using different fishing methods.
I would like to merge rows based on Species (that's if they are the same fish species), if they are caught by both Bottom fishing and Trolling methods it will result in two rows collapsing into one row, changing the Method value to Both.
For example Caranx ignobilis will have a new Method value of Both. Bait Released and Kept columns should also have values on the same row.
ANSWER
Answered 2020-Apr-29 at 12:56This should get you started. You can add the other columns to the summarize function.
QUESTION
Calculate new values based on multiple conditions from other columns
Asked 2018-Apr-05 at 11:45
A filtered data set is provided here:
...ANSWER
Answered 2018-Apr-05 at 11:45Here is a possible approach:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Caranx
You can download it from GitHub.
You can use Caranx 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.
You can use Caranx 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.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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