🎰 GitHub - Lertos/CoinFlip: A coin flip plugin for Minecraft

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Plugin Coinflip. Add To Favorites 6 Servers. Bukkit and Craftbukkit is not affiliated with Minecraft Multiplayer. All images and plugin description are property of the.


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my coinflip plugin

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Plugin Coinflip. Add To Favorites 6 Servers. Bukkit and Craftbukkit is not affiliated with Minecraft Multiplayer. All images and plugin description are property of the.


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At the current coinflip plugin, you must know the username of the user who posted the cf. I reccomend using this CF plugin.


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Plugin name: CoinFlipPlugin link: almarehotel.ru: CoinFlip plugin would be so fun to have on Pocketmine servers.


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Produce tensor filled with 0s and 1s - results of random coin flip, usable as an argument for select ops. Supported backends class almarehotel.ruh.


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Results are two tensors: EncodedBBoxes containing M encoded bounding boxes as [l,t,r,b] , where M is number of anchors and EncodedLabels containing the corresponding label for each encoded box. The color vector is projected along the neutral gray axis, rotated according to hue delta and scaled according to value and saturation multiplers, and then restored to original color space. If used with mixed device, the operator will use a dedicated hardware decoder if available. To return a batch of copies of the same tensor, use nvidia. It is mutually exclusive with providing a value for normalized. If the source is a callable and has a positional argument, it is assumed to be the current iteration number and consecutive calls will be source 0 , source 1 , etc. Operator for horizontal or vertical flip mirror of bounding boxes. It is represented as absolute value. The operator only performs meaningful work at first invocation - subsequent calls will return a reference to the same memory. That is:. Transforms bounding boxes so that they are in the same place in the image after pasting it onto a larger canvas. The memory will be preallocated if it uses GPU or page-locked memory. One erase region with an anchor specified in normalized coordinates and shape in absolute coordinates. Execute a python function that operates on DLPack tensors. Read data from a COCO dataset composed of directory with images and an annotation files. Required when sparse labels are used. All coordinates are in the image coordinate system i. The data is then reshaped according to the shape argument. This means they can be parametrized during operator construction with some Python values or driven by output of other operator when running the pipeline. Perform a fused resize, crop, mirror operation. A polygon is a list of points 2 floats. This parameter helps to avoid reallocation in nvJPEG whenever a bigger image is encountered and internal buffer needs to be reallocated to decode it. Otherwise, StopIteration will be raised when end of data is reached. One erase region with normalized coordinates in the height and width dimensions is provided. Sequences means that the operator can work produce or accept as an input sequence video like kind of input. Should be set to false only if the called function schedules the device job to the stream used by DALI. Images below will use the nvJPEG full host huffman decoder.

Outputs of CPU operators may be used as regular inputs and to provide per-sample parameters for other operators through tensor arguments.

Handles both fixed and random resizing and cropping. Decode images and extract a fixed region-of-interest ROI specified by coinflip plugin constant window dimensions and a variable anchor.

Their outputs may only be used as regular inputs for other GPU operators and pipeline outputs. The op will keep the aspect ratio of the original image. If downmixing is turned on, decoder will produce always 1-D output. Decode audio data. Possible values are:. FileReader supports flat directory structure. The operator can be automatically instantiated in Python with a call to types. Constant value, dtype, shape, layout. Can be also an array of size 2, where the two elements are maximum size per dimension H, W. Normalization takes input image and produces output using formula:. Value between 0 and 1. The optimal workload will depend on the number of threads given to the DALI pipeline and should be found empirically. In the latter case, the generator function will be called again when more data is requested than was yielded by the function. Produce tensor filled with 0s and 1s - results of random coin flip, usable as an argument for select ops. The range for the channel dimension goes from 0 to 3, as it was not specified. To be increased when pipeline processing is CPU stage-bound, trading memory consumption for better interleaving with the Loader thread. The value can be a scalar, a tuple, a list or a numpy array, in which case the shape and dtype if not explicitly overridden , will be taken from that array. A single fill value is provided for all the channels. In such case the output of the loader will be empty. Paste coordinates are normalized so that 0,0 aligns the image to top-left of the canvas and 1,1 aligns it to bottom-right. If set and not empty, the layout must match the dimensionality of the output. For jpeg images, the implementation will use nvJPEG library or libjpeg-turbo depending on the selected backend mixed and cpu respectively. Each pixel in the erased regions is filled with a multi-channel value , , 0. It supports most of well-known audio formats wav, flac, ogg. The coordinates can be transformed to the absolute by multiplying by the input shape. Might be specified as a single value e. For a given sample, the polygons are represented by two tensors:. Non-specified dimensions are treated as if the whole range of the axis was provided. The simplest and preferred way is to specify a source , which may be a callable or iterable. The data is a flat vector of values or a single scalar. This operator is a generic way of handling encoded data in DALI. Encodes input bounding boxes and labels using set of default boxes anchors passed during op construction. It means that the remainder of the batch or even the whole batch can be artificially added when the data set size is not equally divisible by the number of shards, and the shard is not equally divisible by the batch size. Constant , which is more performant. This operator performs HSV manipulation. If the source is a generator function, it is invoked and treated as an iterable - however, unlike a gnerator, it can be used with cycle , in which case the function will be called again when the generator reaches end of iteration. Each mask can be one or more polygons. The source is polled for data via a call source or next source whenever the pipeline needs input for the next iteration. Only the relevant dimensions are specified. To specify multiple regions, anchor and shape represent multiple points consecutively e. Please refer to class nvidia. The erase region covers the range from 10 to in the vertical dimension heigth and goes from 20 to in the horizontal dimension width. RGB — The color space of output image. The function should not modify input tensors. If not set, the data is assumed to be 1D. List of floats in ltrb format. Backprojects the desired crop through the resize operation to reduce the amount of work performed. If the data is scalar, it will be broadcast to fill the entire shape. RGB — The color space of input and output image. Warm up time for threshold policy is 1 epoch. When decoder caching is used, it reduces significantly the amount of data to be cached, but could affect accuracy in some cases. Keep in mind, that hue has additive delta argument, while for saturation and value they are multiplicative. BoxEncoder for full documentation. By default same data type as the input will be used. UINT8 — Output data type; if not set, the input type is used. This operator does not accept any TensorList inputs. For example:. The region is specified by an anchor starting point and a shape dimensions. Other image formats are decoded with OpenCV or other specific libraries e. Input: Bounding box coordinates; in either [x, y, w, h] or [left, top, right, bottom] format. If not set, the output is float if fdata argument is used and int if idata is used. When traversing subdirectories, labels are assigned consecutive numbers. This flag requires that source is either a collection, i. For performance reasons, the operation is approximated by a linear transform in RGB space. Transforms coordinates so that they are flipped point reflected with respect to a center point. False for for width-height representation. Note: If left empty, "x" , "xy" or "xyz" will be assumed, depending on the number of dimensions. In the end, the shard size will be equalized between shards. The floating point input data should be placed in fdata argument and integer data in idata.