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Add cleanup mode to stitcher
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@ -30,7 +30,8 @@ example list of files:
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- Or run the program with parameters:
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- Or run the program with parameters:
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- `divide int`
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- `divide int`
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A downscaling factor. 2 will produce an image with half the side lengths. (default 1)
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A downscaling factor. 2 will produce an image with half the side lengths. (default 1)
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- `input string`The source path of the image tiles to be stitched. (default "..\\..\\output")
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- `input string`
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The source path of the image tiles to be stitched. (default "..\\..\\output")
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- `output string`
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- `output string`
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The path and filename of the resulting stitched image. (default "output.png")
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The path and filename of the resulting stitched image. (default "output.png")
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- `xmax int`
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- `xmax int`
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@ -43,6 +44,8 @@ example list of files:
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Upper bound of the output rectangle. This coordinate is included in the output.
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Upper bound of the output rectangle. This coordinate is included in the output.
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- `prerender`
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- `prerender`
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Pre renders the image in RAM before saving. Can speed things up if you have enough RAM.
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Pre renders the image in RAM before saving. Can speed things up if you have enough RAM.
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- `cleanup float`
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Enables cleanup mode with the given float as threshold. This will **DELETE** images from the input folder; no stitching will be done in this mode. A good value to start with is `0.999`, which deletes images where the sum of the min-max difference of each sub-pixel overlapping with other images is less than 99.9%% of the maximum possible sum of pixel differences.
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To output the 100x100 area that is centered at the origin use:
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To output the 100x100 area that is centered at the origin use:
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@ -50,6 +53,12 @@ To output the 100x100 area that is centered at the origin use:
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./stitch -divide 1 -xmin -50 -xmax 50 -ymin -50 -ymax 50
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./stitch -divide 1 -xmin -50 -xmax 50 -ymin -50 -ymax 50
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```
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```
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To remove images that would cause artifacts (You should recapture the deleted images afterwards):
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``` Shell Session
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./stitch -cleanup 0.999
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```
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To enter the parameters inside of the program:
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To enter the parameters inside of the program:
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``` Shell Session
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``` Shell Session
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@ -26,6 +26,8 @@ type imageTile struct {
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image image.Image // Either a rectangle or an RGBA image. The bounds of this image are determined by the filename.
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image image.Image // Either a rectangle or an RGBA image. The bounds of this image are determined by the filename.
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imageMutex *sync.RWMutex //
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imageMutex *sync.RWMutex //
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imageUsedFlag bool // Flag signalling, that the image was used recently
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imageUsedFlag bool // Flag signalling, that the image was used recently
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pixelErrorSum uint64 // Sum of the difference between the (sub)pixels of all overlapping images. 0 Means that all overlapping images are identical.
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}
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}
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func (it *imageTile) GetImage() (*image.RGBA, error) {
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func (it *imageTile) GetImage() (*image.RGBA, error) {
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@ -104,7 +104,7 @@ func Stitch(tiles []imageTile, destImage *image.RGBA) error {
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return nil
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return nil
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}
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}
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// StitchGrid calls stitch, but divides the workload into a grid of chunks.
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// StitchGrid calls Stitch, but divides the workload into a grid of chunks.
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// Additionally it runs the workload multithreaded.
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// Additionally it runs the workload multithreaded.
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func StitchGrid(tiles []imageTile, destImage *image.RGBA, gridSize int, bar *pb.ProgressBar) (errResult error) {
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func StitchGrid(tiles []imageTile, destImage *image.RGBA, gridSize int, bar *pb.ProgressBar) (errResult error) {
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//workloads := gridifyRectangle(destImage.Bounds(), gridSize)
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//workloads := gridifyRectangle(destImage.Bounds(), gridSize)
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@ -207,3 +207,124 @@ func drawMedianBlended(images []*image.RGBA, destImage *image.RGBA) {
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}
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}
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}
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}
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}
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}
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// Compare takes a list of tiles and compares them pixel by pixel.
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// The resulting pixel difference sum is stored in each tile.
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func Compare(tiles []imageTile, bounds image.Rectangle) error {
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intersectTiles := []*imageTile{}
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images := []*image.RGBA{}
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// Get only the tiles that intersect with the bounds.
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// Ignore alignment here, doesn't matter if an image overlaps a few pixels anyways.
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for i, tile := range tiles {
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if tile.OffsetBounds().Overlaps(bounds) {
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tilePtr := &tiles[i]
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intersectTiles = append(intersectTiles, tilePtr)
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img, err := tilePtr.GetImage()
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if err != nil {
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return fmt.Errorf("Couldn't get image: %w", err)
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}
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imgCopy := *img
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imgCopy.Rect = imgCopy.Rect.Add(tile.offset).Inset(4) // Reduce image bounds by 4 pixels on each side, because otherwise there will be artifacts.
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images = append(images, &imgCopy)
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}
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}
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tempTilesEmpty := make([]*imageTile, 0, len(intersectTiles))
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for iy := bounds.Min.Y; iy < bounds.Max.Y; iy++ {
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for ix := bounds.Min.X; ix < bounds.Max.X; ix++ {
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var rMin, rMax, gMin, gMax, bMin, bMax uint8
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point := image.Point{ix, iy}
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found := false
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tempTiles := tempTilesEmpty
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// Iterate through all images and find min and max subpixel values.
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for i, img := range images {
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if point.In(img.Bounds()) {
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tempTiles = append(tempTiles, intersectTiles[i])
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col := img.RGBAAt(point.X, point.Y)
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if !found {
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found = true
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rMin, rMax, gMin, gMax, bMin, bMax = col.R, col.R, col.G, col.G, col.B, col.B
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} else {
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if rMin > col.R {
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rMin = col.R
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}
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if rMax < col.R {
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rMax = col.R
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}
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if gMin > col.G {
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gMin = col.G
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}
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if gMax < col.G {
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gMax = col.G
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}
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if bMin > col.B {
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bMin = col.B
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}
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if bMax < col.B {
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bMax = col.B
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}
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}
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}
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}
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// If there were no images to get data from, ignore the pixel.
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if !found {
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continue
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}
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// Write the error value back into the tiles (Only those that contain the point point)
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for _, tile := range tempTiles {
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tile.pixelErrorSum += uint64(rMax-rMin) + uint64(gMax-gMin) + uint64(bMax-bMin)
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}
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}
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}
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return nil
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}
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// CompareGrid calls Compare, but divides the workload into a grid of chunks.
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// Additionally it runs the workload multithreaded.
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func CompareGrid(tiles []imageTile, bounds image.Rectangle, gridSize int, bar *pb.ProgressBar) (errResult error) {
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//workloads := gridifyRectangle(destImage.Bounds(), gridSize)
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workloads, err := hilbertifyRectangle(bounds, gridSize)
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if err != nil {
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return err
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}
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if bar != nil {
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bar.SetTotal(int64(len(workloads))).Start()
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}
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// Start worker threads
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wc := make(chan image.Rectangle)
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wg := sync.WaitGroup{}
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for i := 0; i < runtime.NumCPU()*2; i++ {
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wg.Add(1)
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go func() {
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defer wg.Done()
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for workload := range wc {
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if err := Compare(tiles, workload); err != nil {
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errResult = err // This will not stop execution, but at least one of any errors is returned.
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}
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if bar != nil {
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bar.Increment()
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}
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}
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}()
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}
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// Push workload to worker threads
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for _, workload := range workloads {
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wc <- workload
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}
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// Wait until all worker threads are done
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close(wc)
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wg.Wait()
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return
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}
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@ -28,6 +28,7 @@ var flagYMin = flag.Int("ymin", 0, "Upper bound of the output rectangle. This co
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var flagXMax = flag.Int("xmax", 0, "Right bound of the output rectangle. This coordinate is not included in the output.")
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var flagXMax = flag.Int("xmax", 0, "Right bound of the output rectangle. This coordinate is not included in the output.")
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var flagYMax = flag.Int("ymax", 0, "Lower bound of the output rectangle. This coordinate is not included in the output.")
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var flagYMax = flag.Int("ymax", 0, "Lower bound of the output rectangle. This coordinate is not included in the output.")
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var flagPrerender = flag.Bool("prerender", false, "Pre renders the image in RAM before saving. Can speed things up if you have enough RAM.")
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var flagPrerender = flag.Bool("prerender", false, "Pre renders the image in RAM before saving. Can speed things up if you have enough RAM.")
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var flagCleanupThreshold = flag.Float64("cleanup", 0, "Enable cleanup mode with the given threshold. This will DELETE images from the input folder, no stitching will be done in this mode. A good value to start with is 0.999, which deletes images where the sum of the min-max difference of each sub-pixel overlapping with other images is less than 99.9%% of the maximum possible sum of pixel differences.")
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func main() {
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func main() {
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flag.Parse()
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flag.Parse()
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@ -142,6 +143,63 @@ func main() {
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outputRect = image.Rect(xMin, yMin, xMax, yMax)
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outputRect = image.Rect(xMin, yMin, xMax, yMax)
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}
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}
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// Query the user, if there were no cmd arguments given
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/*if flag.NFlag() == 0 {
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fmt.Println("\nYou can now define a cleanup threshold. This mode will DELETE input images based on their similarity with other overlapping input images. The range is from 0, where no images are deleted, to 1 where all images will be deleted. A good value to get rid of most artifacts is 0.999. If you enter a threshold above 0, the program will not stitch, but DELETE some of your input images. If you want to stitch, enter 0.")
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prompt := promptui.Prompt{
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Label: "Enter cleanup threshold:",
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Default: strconv.FormatFloat(*flagCleanupThreshold, 'f', -1, 64),
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AllowEdit: true,
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Validate: func(s string) error {
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result, err := strconv.ParseFloat(s, 64)
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if err != nil {
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return err
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}
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if result < 0 || result > 1 {
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return fmt.Errorf("Number %v outside of valid range [0;1]", result)
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}
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return nil
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},
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}
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result, err := prompt.Run()
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if err != nil {
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log.Panicf("Error while getting user input: %v", err)
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}
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*flagCleanupThreshold, err = strconv.ParseFloat(result, 64)
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if err != nil {
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log.Panicf("Error while parsing user input: %v", err)
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}
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}*/
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if *flagCleanupThreshold < 0 || *flagCleanupThreshold > 1 {
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log.Panicf("Cleanup threshold (%v) outside of valid range [0;1]", *flagCleanupThreshold)
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}
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if *flagCleanupThreshold > 0 {
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bar := pb.Full.New(0)
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log.Printf("Cleaning up %v tiles at %v", len(tiles), outputRect)
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if err := CompareGrid(tiles, outputRect, 512, bar); err != nil {
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log.Panic(err)
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}
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bar.Finish()
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for _, tile := range tiles {
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pixelErrorSumNormalized := float64(tile.pixelErrorSum) / float64(tile.Bounds().Size().X*tile.Bounds().Size().Y*3*255)
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if 1-pixelErrorSumNormalized <= *flagCleanupThreshold {
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os.Remove(tile.fileName)
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log.Printf("Tile %v has matching factor of %f. Deleted file!", &tile, 1-pixelErrorSumNormalized)
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} else {
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log.Printf("Tile %v has matching factor of %f", &tile, 1-pixelErrorSumNormalized)
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}
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}
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return
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}
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// Query the user, if there were no cmd arguments given
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// Query the user, if there were no cmd arguments given
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if flag.NFlag() == 0 {
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if flag.NFlag() == 0 {
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prompt := promptui.Prompt{
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prompt := promptui.Prompt{
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