I've been google-searching trying to find an approach, or a set of existing tools, for taking a mercator raster data-tile and converting it to a vector tile (by, for instance, creating polygon-like iso-line features via marching squares or whatever and packing it into a protocol buffer). I have a web-mercator backend service that produces raster png tiles (of raster weather data), and I would like to figure-out how to also create vector tiles from the same tile data, on the fly preferably.
Mapbox-ish/Mapnik tool-sets seem like a natural starting point, but I'm just going to ask here to see if anyone can set me on the immediate right path. It's not obvious to me from googling around.
Related
I'm struggling with a texture-baking process with 3DSmax software. I have a white 3D mesh with 2 image textures. I'm trying to get a diffusemap (see target_diffuse_map.jpg). To do this, I exectue the following steps:
1) Affect image-texture1 and image-texture2 to face1 and face2 of the objet.
2) Clone the object to get the white colors when baking texture.
3) unwrap UVM.
4) Rendering Texture to obtain the diffuse map.
5) Projection of the texture + white colors on the cloned object.
Please, find these steps on this small video I made: https://drive.google.com/file/d/1h4v2CrL8OCLwdeVtLmpQwD250cawgJpi/view
I obtain a bad sampled and weird diffuse map (please see obtained_diffuse_map.jpg). What I want is target_diffuse_map.jpg.
I'm I forgetting some steps?
Thank you for your help.
You need to either:
Add a small amount of "Push" in the Projection Modifier
Uncheck "Use Cage" in the Projection Options dialog, while setting a very small value for the offset
Projection Mapping works by casting rays from points on the cage towards corresponding model points on your mesh. You did not push the cage out at all, therefore rays are not well defined; rays are cast from a point toward a direction which is the exact same point. This causes numerical errors and z-fighting. The there needs to be some time amount of push so the "from" and "to" points of each ray are different giving them a well-defined direction to travel.
The second option, instead of using the cage defined in the projection modifier, is to use the offset method (you probably still need to apply projection modifier though). This method defines each rays as starting from a point defined by taking the model point of the mesh and moving outward by a fixed offset amount in the direction of the normal. The advantage is that for curved objects with large polygons, it produces less distortion because the system uses the smoothed shading normal at each point. The disadvantage you can't have different cage distances at different points of the model, for better control. Use this method for round wooden barrels and other simplistic objects with large, smooth curves.
Also, your situation is made difficult by having different parts of the model very close to each other (touching) and embedded within each other - namely how the mouth of the bottle is inside the cap and the cap it touching the base. For this case, it might make sense to break the objects apart after you have the overall UV mapping, run projection mapping separately on each one separately, and then combine the maps back together in an image editor.
I've been trying without success to extract face features, for instance the mouth, from ARSCNFaceGeometry in order to change their color or add a different material.
I understand I need to create an SCNGeometry for which I have the SCNGeometrySource but haven't been able to create the SCNGeometryElement.
Have tried creating it from ARFaceAnchor in update(from faceGeometry: ARFaceGeometry) but so far have been unable.
Would really appreciate someone help
ARSCNFaceGeometry is a single mesh. If you want different areas of it to be different colors, your best bet is to apply a texture map (which you do in SceneKit by providing images for material property contents).
There’s no semantic information associated with the vertices in the mesh — that is, there’s nothing that says “this point is the tip of the nose, these points are the edge of the upper lip, etc”. But the mesh is topologically stable, so if you create a texture image that adds a bit of color around the lips or a lightning bolt over the eye or whatever, it’ll stay there as the face moves around.
If you need help getting started on painting a texture, there are a couple of things you could try:
Create a dummy texture first
Make a square image and fill it with a double gradient, such that the red and blue component for each pixel is based on the x and y coordinate of that pixel. Or some other distinctive pattern. Apply that texture to the model, and see how it looks — the landmarks in the texture will guide you where to paint.
Export the model
Create a dummy ARSCNFaceGeometry using the init(blendShapes:) initializer and an empty blendShapes dictionary (you don’t need an active ARFaceTracking session for this, but you do need an iPhone X). Use SceneKit’s scene export APIs (or Model I/O) to write that model out to a 3D file of some sort (.scn, which you can process further on the Mac, or something like .obj).
Import that file into your favorite 3D modeling tool (Blender, Maya, etc) and use that tool to paint a texture. Then use that texture in your app with real faces.
Actually, the above is sort of an oversimplification, even though it’s the simple answer for common cases. ARSCNFaceGeometry can actually contain up to four submeshes if you create it with the init(device:fillMesh:) initializer. But even then, those parts aren’t semantically labeled areas of the face — they’re the holes in the regular face model, flat fill-ins for the places where eyes and mouth show through.
I'm currently working on a project where I need to be able to very reliable get the positions of the balls on a pool table.
I'm using a Kinect v2 above the table as the source.
Initial image looks like this (after converting it to 8-bit from 16-bit by throwing away pixels which is not around table level):
Then a I subtract a reference image with the empty table from the current image.
After thresholding and equalization it looks like this: image
It's fairly easy to detect the individual balls on a single image, the problem is that I have to do it constantly with 30fps.
Difficulties:
Low resolution image (512*424), a ball is around 4-5 pixel in diameter
Kinect depth image has a lot of noise from this distance (2 meters)
Balls look different on the depth image, for example the black ball is kind of inverted compared to the others
If they touch each other then they can become one blob on the image, if I try to separate them with depth thresholding (only using the top of the balls) then some of the balls can disappear from the image
It's really important that anything other than balls should not be detected e.g.: cue, hands etc...
My process which kind of works but not reliable enough:
16bit to 8bit by thresholding
Subtracting sample image with empty table
Cropping
Thresholding
Equalizing
Eroding
Dilating
Binary threshold
Contour finder
Some further algorithms on the output coordinates
The problem is that a pool cue or hand can be detected as a ball and also if two ball touches then it can cause issues. Also tried with hough circles but with even less success. (Works nicely if the Kinect is closer but then it cant cover the whole table)
Any clues would be much appreciated.
Expanding comments above:
I recommend improving the IRL setup as much as possible.
Most of the time it's easier to ensure a reliable setup than to try to "fix" that user computer vision before even getting to detecting/tracking anything.
My suggestions are:
Move the camera closer to the table. (the image you posted can be 117% bigger and still cover the pockets)
Align the camera to be perfectly perpendicular to the table (and ensure the sensor stand is sturdy and well fixed): it will be easier to process a perfect top down view than a slightly tilted view (which is what the depth gradient shows). (sure the data can be rotated, but why waste CPU cycles when you can simply keep the sensor straight)
With a more reliable setup you should be able to threshold based on depth.
You can possible threshold to the centre of balls since the information bellow is occluded anyway. The balls do not deform, so it the radius decreases fast the ball probably went in a pocket.
One you have a clear threshold image, you can findContours() and minEnclosingCircle(). Additionally you should contrain the result based on min and max radius values to avoid other objects that may be in the view (hands, pool cues, etc.). Also have a look at moments() and be sure to read Adrian's excellent Ball Tracking with OpenCV article
It's using Python, but you should be able to find OpenCV equivalent call for the language you use.
In terms tracking
If you use OpenCV 2.4 you should look into OpenCV 2.4's tracking algorithms (such as Lucas-Kanade).
If you already use OpenCV 3.0, it has it's own list of contributed tracking algorithms (such as TLD).
I recommend starting with Moments first: use the simplest and least computationally expensive setup initially and see how robuts the results are before going into the more complex algorithms (which will take to understand and get the parameters right to get expected results out of)
We are planning to create a surface damage detection prototype for ceramic tiles with surface discoloration as a specific damage through the use of OpenCV. We would like to know what method should we consider using. We are new into developing these types of object recognition/object tracking programs. We've read about methods such as the Histogram method and the one where the Hue saturation value was being tracked, but still we are confused.
Also, we would like to know whether it is possible to detect the Hue saturation value of an object without the use of track bars.
Any relevant and helpful response will be greatly appreciated.
I think you can do it in sequence:
1) find tile region. Use corners detector, hough lines, etc.
2) find SIFT (or other descriprors) and recognize what image must be on this tile (find it in you tiles images database).
3) align images carefully. For example find homograpy between found in DB image and image of tile from camera (using SIFT features).
4) find color distance between every pixel in tile image from camera and tile image from database.
5) threshold differences by some value -> get problematic regions
And think about lighting. You have to provide equal lighting conditions for you measurements.
I need to paint a square image, mapped or transformed to an unknown-at-compile-time four-sided polygon. How can I do this?
Longer explanation
The specific problem is rendering a map tile with a non-rectangular map projection. Suppose I have the following tile:
and I know the four corner points need to be here:
Given that, I would like to get the following output:
The square tile may be:
Rotated; and/or
Be narrower at one end than at the other.
I think the second item means this requires a non-affine transformation.
Random extra notes
Four-sided? It is plausible that to be completely correct, the tile should be
mapped to a polygon with more than four points, but for our purposes
and at the scale it is drawn, a square -> other four-cornered-polygon
transformation should be enough.
Why preferably GDI only? All rendering so far is done using GDI, and I want to keep the code (a) fast and (b) requiring as few extra
libraries as possible. I am aware of some support for
transformations in GDI and have been experimenting with them
today, but even after experimenting with them I'm not sure if they're
flexible enough for this purpose. If they are, I haven't managed to
figure it out, and so I'd really appreciate some sample code.
GDI+ is also ok since we use it elsewhere, but I know it can be slow, and speed is
important here.
One other alternative is anything Delphi- /
C++Builder-specific; this program is written mostly in C++ using
the VCL, and the graphics in question are currently painted to a
TCanvas with a mix of TCanvas methods and raw WinAPI/GDI calls.
Overlaying images: One final caveat is that one colour in the tile may be for color-key
transparency: that is, all the white (say) squares in the above tile
should be transparent when drawn over whatever is underneath.
Currently, tiles are drawn to square or axis-aligned rectangular
targets using TransparentBlt.
I'm sorry for all the extra caveats that make this question more complicated
than 'what algorithm should I use?' But I will happily accept answers with
only algorithmic information too.
You might also want to have a look at Graphics32.
The screen shot bewlow shows how the transfrom demo in GR32 looks like
Take a look at 3D Lab Vector graphics. (Specially "Football field" in the demo).
Another cool resource is AggPas with full source included (download)
AggPas is Open Source and free of charge 2D vector graphics library. It is an Object Pascal native port of the Anti-Grain Geometry library - AGG, originally written by Maxim Shemanarev in C++. AggPas doesn't depend on any graphic API or technology. Basically, you can think of AggPas as of a rendering engine that produces pixel images in memory from some vectorial data.
Here is how the perspective demo looks like:
After transformation:
The general technique is described in George Wolberg's "Digital Image Warping". It looks like this abstract contains the relevant math, as does this paper. You need to create a perspective matrix that maps from one quad to another. The above links show how to create the matrix. Once you have the matrix, you can scan your output buffer, perform the transformation (or possibly the inverse - depending on which they give you), and that will give you points in the original image that you can copy from.
It might be easier to use OpenGL to draw a textured quad between the 4 points, but that doesn't use GDI like you wanted.