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Find centralized, trusted content and collaborate around the technologies you use most. Connect and share knowledge within a single location that is structured and easy to search. After installation of Android SDK, the folder. As far as I know, this is the default folder of Android Virtual Devices for configuration files. You can override the defaults by setting the following environment variables.
Otherwise the default path will be chosen. But it is not necessary to include. The AVD Manager creates a. If you go for this answer be aware of this note : Starting with Android Studio 4. In addition to the answer provided by Dariusz Bacinski , you have to include the. It was not working for me if I did not include the.
If you want to move just the AVD folder and not everything else, use those environmental variables. You might want to specify a new location if the default location is low on disk space. Stack Overflow for Teams — Start collaborating and sharing organizational knowledge. Create a free Team Why Teams? Learn more about Teams. Moving default AVD configuration folder. Asked 12 years, 1 month ago.
Modified 7 days ago. Viewed 94k times. How can I move. Dariusz Bacinski. Dariusz Bacinski Dariusz Bacinski 7, 8 8 gold badges 36 36 silver badges 46 46 bronze badges. Possible duplicate of Possible to change where Android Virtual Devices are saved? Add a comment. Sorted by: Reset to default. Highest score default Trending recent votes count more Date modified newest first Date created oldest first. I’ve found the answer. Add New variable. Thank you, this worked for me.
I was running out of space on C: where it initially put all the AVD files and was causing other problems with the computer. Thanks a lot. It did NOT work when I added it as a new environment variable. I had to make sure.
This makes sense to me as the. Show 5 more comments. Thanks, exactly what I was looking for. I confirmed these instructions are correct as of Android Studio 2. As long as your. It can be a user or system environment variable — Xcalibur. Dariusz Bacinski 7, 8 8 gold badges 36 36 silver badges 46 46 bronze badges. I’ve tried both, still not working for me either way.
I have a honeycomb tablet and a gingerbread phone to test on, but one of my computers doesn’t like Motorola’s drivers for whatever reason, so I need an AVD. Changing the debug keystore from default seems to have solved the problem for some reason. This is not correct – it will look for a. See the answer below — Xcalibur. On windows it can be your user directory. Dennis Maina Dennis Maina 13 5 5 bronze badges.
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Default folder x 5 free. Default Folder X 5.7b2 Crack
Figure 1. Before left and after right having applied the alignment procedure to an eye fundus. The purpose of this plugin is to register—in other words, to align or to match—two images, one of them being called the source image and the other the target image. Three alignment modes are available: manual, automatic, and batch.
In all three cases, the user is given the opportunity to interactively specify some landmarks, which establishes the initial correspondence between the images. In the automatic and batch modes, the landmarks of the source image are then automatically refined to better match those of the target image.
In the manual mode, this automatic refinement procedure is disengaged. Most of the time, the automatic algorithm requires no user input because it is robust enough that the default initial conditions are sufficiently accurate. After completion of the registration process, the plugin uses the final position of the source and target landmarks to create a warped image that has the size of the target and that contains a distorted version of the source.
The distortion is such that the landmarks of the source are mapped to those of the target. In the automatic and batch modes, the landmarks of the source have been refined to minimize the mean-square difference between the target and the warped image. The plugin can also be called by a macro or by another plugin. In the latter case, the registration can proceed silently if desired, and the registration results can be retrieved for further processing.
This distribution is dated July 7, It includes the complete set of source files, along with the precompiled classes and the application programming interface. This set of Java classes is based on the following paper: P. Ruttimann, M. It is written as a plugin for ImageJ. Please read the ImageJ documentation to learn how to install plugins. The position of the landmarks can be stored and retrieved. However, the size of the source and target images is checked upon landmark retrieval; a mismatch is disallowed.
The computations may favor either speed or accuracy. If speed is favored, then one of several consequences is that the warped image is computed from the source by nearest-neighbor interpolation. If accuracy is favored, then one of several consequences is that cubic-spline interpolation is performed instead.
The plugin can accommodate grayscale images and RBG stacks. Only one color plane of the RGB stack is taken into account for registration; the transformation applied to the two remaining color planes will be adjusted accordingly. Manual and automatic modes: if a stack of grayscale images is selected, only the first slice is registered. The second slice, if any, acts as a boolean mask, with the following convention: the presence of a zero value in the second slice of either image indicates that the data [at the same location in the first slice of both images] should not be considered for automatic alignment; the presence of values that are jointly nonzero in the second slice of both images indicates that the data [at the same location in the first slice of both images] are relevant and should indeed participate in the mean-square computation.
By convention, the data outside the initial image frames are considered as irrelevant, while every pixel within the initial image frames is considered relevant. When the source image is an RGB stack, the output image that results from the registration process is returned as an RGB color image. Else, it is returned as a stack where the first slice contains the source image after the warping has been applied, and where the second slice contains the source mask after warping.
A nearest-neighbor interpolation is used for the source mask. The output type is either RGB or float bit. To know the exact domain where the mean-square criterion has been applied, the user must himself perform an “AND” operation between the mask if any of the target image on one hand, and the returned mask of the warped source image on the other hand: the returned mask does not provide the explicit result of this operation, but only one of its two operands.
RGB stacks do not accomodate masks. Batch mode: the target image plays the same role in the batch mode as in the manual or automatic modes. If the target image is a stack, its second slice still defines a registration mask; else, every pixel of the target image is considered relevant.
The source image, however, is treated differently. It has to be a stack for the batch mode to be enabled, and every slice gets registered in turn to the same target image. Each slice is given the same default mask, with every pixel being considered relevant. The output image that results from the registration process is returned as a stack. Each slice contains a warped version of the corresponding slice of the source image.
As in the case of manual and automatic modes, the output type is float bit. The batch mode is not available for RGB stacks. In some situations, a single target is desirable because the source images differ essentially by their geometry, less so by their content. TurboReg is appropriate in those situations. But there also exist cases where the content of the several source images gradually evolves from frame to frame; this might happen for example with a time series, or with a 3D stack of slices that are acquired with only a loose control of the slice-to-slice alignment.
A companion plugin has been written to help in this different settings; it is named StackReg and is available here. To select a point, click anywhere in the source or target image. The point closest to where you clicked will be highlighted. To move points, drag within the image. The point closest to where you clicked will be moved to the position where you release the mouse.
Alternatively, you can use the keyboard arrow keys to get a finer control over the position of the landmarks. Hitting the tab key will change the selection of the current point.
Note: it is not possible to move a point outside of the image frame. For the rigid-body transformation, there are two types of landmark. The green cross determines the translation. The other two landmarks are used to determine the orientation only, as indicated by the blue and brown lines.
To magnify an image, select the magnification tool and click in the image. This dialog box will appear if at least two grayscale images or RGB stacks are available at the time when TurboReg is launched. If that is not the case, a message will inform you of this requirement. If you decide to select as target the current source, your new selection will be honored, but the source image will be changed as well to reflect another arbitrary choice it is not possible to register an image to itself.
If you decide to select as source the current target, your new selection will be honored, but the target image will be changed as well to reflect another arbitrary choice it is not possible to register an image to itself.
When selecting another target or source, or when TurboReg is launched, you may notice some activity in the progress bar of ImageJ. This activity notifies you that some background preprocessing is going on. You can safely ignore it and proceed you don’t have to wait until this preprocessing is complete if you want to perform additional operations. The same applies when switching the distortion type from Bilinear, or to Bilinear. The landmarks are reset to their default position when changing the distortion type.
You can save the current configuration of landmarks in a text file by clicking the button [Save Now The format of the file is rigid; it is nevertheless possible to edit its numerical fields if desired.
This may allow you to overcome the limitation that forbids one to interactively move a point outside of the image frame. You can restore a configuration of landmarks from a text file by clicking the button [Load The configuration must have been previously created by TurboReg.
A check on the current size of the target and source images is performed to ensure that the stored configuration makes sense with respect to the current images. The automatic alignment mode is used to nudge the initial source landmarks, which results in refined landmarks.
Those can be saved by checking the box [Save on Exit]. You can choose one of two different trade-offs between registration speed and accuracy. When speed is favored, the output image suffers from low-quality interpolation nearest-neighbor. Moreover, in the automatic registration mode, the accuracy is further reduced because the refinement of landmarks is made coarser. When accuracy is favored instead, the output image benefits from high-quality interpolation cubic spline.
Moreover, in the automatic registration mode, more effort is spent on refining the landmarks. Please note that it is not possible to perform automatic registration when speed is favored and when at least one of the dimensions of the target or source images is too small; in that case, manual registration is the only mode allowed with the quality set to ‘Fast’.
Else, set the quality to ‘Accurate’. Some additional flexibility is available when calling TurboReg from ImageJ’s macro language, which may be suitable in certain specialized situations. Most importantly, the landmark positions are directly accessible to further processing. Also, it is possible to specify cropping zones in the source and target images, which is useful when there is a reduced overlap between images, a situation that often arises when stitching together a mosaic of images.
Although TurboReg is scriptable, it is not recordable. This corresponds most closely to the automatic mode of the interactive version of TurboReg. The quality is always set to ‘Accurate’. This corresponds most closely to the manual mode of the interactive version of TurboReg. Methods of the returned object myTurboRegObject can then be accessed thanks to a reflection mechanism. This approach facilitates code maintenance, especially the independence of all plugins; moreover, it limits the risk of having duplicate class names inside the hierarchy of folders spanned by ImageJ.
The full description of these three methods and of their parameters is available from the API of TurboReg. A fully developed example of a plugin that takes advantage of the interoperability of TurboReg is StackReg. A technical Javadoc documentation is available.
The dialog box is modeless, which means you have access to all functions of ImageJ. While some actions are safe e. You’ll be free to use this software for research purposes, but you must not transmit and distribute it without our consent.
In addition, you undertake to include a citation or acknowledgment whenever you present or publish results that are based on it.