Calibration frames config

src/vstarstack/library/loaders/yuv.py

@@ -46,7 +46,7 @@ def readyuv(fname: str, width: int, height: int):
             dataframe = vstarstack.library.data.DataFrame(params, tags)
             exptime = 1
 
-            dataframe.add_channel(yuv, "raw", encoded=True)
+            dataframe.add_channel(yuv, "raw", encoded=True, signal=True)
             dataframe.add_parameter("yuv422", "format")
             dataframe.add_parameter(exptime, "weight")
             yield dataframe

src/vstarstack/library/projection/__init__.py

@@ -1,6 +1,7 @@
 from enum import Enum
 
 class ProjectionType(Enum):
+    NoneProjection = 0
     Perspective = 1
     Orthographic = 2
     Equirectangular = 3

src/vstarstack/library/projection/tools.py

@@ -23,7 +23,9 @@
 
 def add_description(dataframe : vstarstack.library.data.DataFrame, projection : ProjectionType, **argv):
     """Add projection description to dataframe"""
-    if projection == ProjectionType.Perspective:
+    if projection == ProjectionType.NoneProjection:
+        name = "none"
+    elif projection == ProjectionType.Perspective:
         F = argv["F"]
         kw = argv["kw"]
         kh = argv["kh"]
@@ -51,7 +53,9 @@ def extract_description(dataframe : vstarstack.library.data.DataFrame) -> typing
     """Extract projection description from dataframe"""
     projection = dataframe.get_parameter("projection")
     if projection is None:
-        return None
+        return None, {}
+    elif projection == "none":
+        return ProjectionType.NoneProjection, {}
     elif projection == "perspective":
         return ProjectionType.Perspective, {
             "F" : dataframe.get_parameter("projection_perspective_F"),
@@ -75,7 +79,10 @@ def build_projection(projection: ProjectionType, desc : dict, shape : tuple):
     w = shape[1]
     h = shape[0]
 
-    if projection == ProjectionType.Perspective:
+    if projection == ProjectionType.NoneProjection:
+        raise Exception("Trying to build \"NoneProjection\"")
+
+    elif projection == ProjectionType.Perspective:
         F = desc["F"]
         kw = desc["kw"]
         kh = desc["kh"]
@@ -91,6 +98,9 @@ def build_projection(projection: ProjectionType, desc : dict, shape : tuple):
         rot = desc["rot"]
         return OrthographicProjection(w, h, a, b, angle, rot)
 
+    else:
+        raise Exception("Trying to build some unknown projection")
+
 def get_projection(dataframe : vstarstack.library.data.DataFrame):
     """Get projection from dataframe"""
     projection, desc = extract_description(dataframe)

src/vstarstack/tool/calibration.py

@@ -22,6 +22,7 @@
 import vstarstack.library.calibration.dark
 import vstarstack.library.calibration.flat
 
+# applying flats
 def _process_file_flatten(input_fname : str,
                           flat : vstarstack.library.data.DataFrame,
                           output_fname : str):
@@ -31,17 +32,6 @@ def _process_file_flatten(input_fname : str,
     vstarstack.tool.common.check_dir_exists(output_fname)
     result.store(output_fname)
 
-def _process_file_remove_dark(input_fname : str,
-                              dark : vstarstack.library.data.DataFrame,
-                              output_fname : str):
-    print(f"Processing {input_fname}")
-    dataframe = vstarstack.library.data.DataFrame.load(input_fname)
-    result = vstarstack.library.calibration.dark.remove_dark(dataframe, dark)
-    if result is None:
-        print(f"Can not remove dark from {input_fname}")
-    vstarstack.tool.common.check_dir_exists(output_fname)
-    result.store(output_fname)
-
 def _process_dir_flatten(input_path : str,
                          flat : vstarstack.library.data.DataFrame,
                          output_path : str):
@@ -51,14 +41,6 @@ def _process_dir_flatten(input_path : str,
         args = [(filename, flat, os.path.join(output_path, name + ".zip")) for name, filename in files]
         pool.starmap(_process_file_flatten, args)
 
-def _process_dir_remove_dark(input_path : str,
-                      dark : vstarstack.library.data.DataFrame,
-                      output_path : str):
-    files = vstarstack.tool.common.listfiles(input_path, ".zip")
-    with mp.Pool(vstarstack.tool.cfg.nthreads) as pool:
-        args = [(filename, dark, os.path.join(output_path, name + ".zip")) for name, filename in files]
-        pool.starmap(_process_file_remove_dark, args)
-
 def _process_flatten(_project : vstarstack.tool.cfg.Project,
                      argv : list[str]):
     input_path = argv[0]
@@ -70,6 +52,26 @@ def _process_flatten(_project : vstarstack.tool.cfg.Project,
     else:
         _process_file_flatten(input_path, flat, output_path)
 
+# applying darks
+def _process_file_remove_dark(input_fname : str,
+                              dark : vstarstack.library.data.DataFrame,
+                              output_fname : str):
+    print(f"Processing {input_fname}")
+    dataframe = vstarstack.library.data.DataFrame.load(input_fname)
+    result = vstarstack.library.calibration.dark.remove_dark(dataframe, dark)
+    if result is None:
+        print(f"Can not remove dark from {input_fname}")
+    vstarstack.tool.common.check_dir_exists(output_fname)
+    result.store(output_fname)
+
+def _process_dir_remove_dark(input_path : str,
+                      dark : vstarstack.library.data.DataFrame,
+                      output_path : str):
+    files = vstarstack.tool.common.listfiles(input_path, ".zip")
+    with mp.Pool(vstarstack.tool.cfg.nthreads) as pool:
+        args = [(filename, dark, os.path.join(output_path, name + ".zip")) for name, filename in files]
+        pool.starmap(_process_file_remove_dark, args)
+
 def _process_remove_dark(_project : vstarstack.tool.cfg.Project,
                          argv : list[str]):
     input_path = argv[0]
@@ -81,31 +83,46 @@ def _process_remove_dark(_project : vstarstack.tool.cfg.Project,
     else:
         _process_file_remove_dark(input_path, dark, output_path)
 
-def _process_build_dark(_project : vstarstack.tool.cfg.Project,
+# building darks
+def _process_build_dark(project : vstarstack.tool.cfg.Project,
                         argv : list[str]):
-    input_path = argv[0]
-    dark_fname = argv[1]
+    if len(argv) >= 2:
+        input_path = argv[0]
+        dark_fname = argv[1]
+    else:
+        input_path = project.config.paths.dark.npy
+        dark_fname = project.config.paths.dark.result
     files = vstarstack.tool.common.listfiles(input_path, ".zip")
     darks = [item[1] for item in files]
     src = vstarstack.library.common.FilesImageSource(darks)
     dark = vstarstack.library.calibration.dark.prepare_darks(src)
     dark.store(dark_fname)
 
-def _process_build_flat_simple(_project : vstarstack.tool.cfg.Project,
+# building flats
+def _process_build_flat_simple(project : vstarstack.tool.cfg.Project,
                                argv : list[str]):
-    input_path = argv[0]
-    flat_fname = argv[1]
+    if len(argv) >= 2:
+        input_path = argv[0]
+        flat_fname = argv[1]
+    else:
+        input_path = project.config.paths.flat.npy
+        flat_fname = project.config.paths.flat.result
     smooth = vstarstack.tool.cfg.get_param("smooth", int, 31)
     files = vstarstack.tool.common.listfiles(input_path, ".zip")
     flats = [item[1] for item in files]
     src = vstarstack.library.common.FilesImageSource(flats)
     flat = vstarstack.library.calibration.flat.prepare_flat_simple(src, smooth)
     flat.store(flat_fname)
 
-def _process_build_flat_sky(_project : vstarstack.tool.cfg.Project,
+def _process_build_flat_sky(project : vstarstack.tool.cfg.Project,
                               argv : list[str]):
-    input_path = argv[0]
-    flat_fname = argv[1]
+    if len(argv) >= 2:
+        input_path = argv[0]
+        flat_fname = argv[1]
+    else:
+        input_path = project.config.paths.flat.npy
+        flat_fname = project.config.paths.flat.result
+
     smooth = vstarstack.tool.cfg.get_param("smooth", int, 31)
     if smooth % 2 == 0:
         smooth += 1
@@ -116,13 +133,18 @@ def _process_build_flat_sky(_project : vstarstack.tool.cfg.Project,
     vstarstack.tool.common.check_dir_exists(flat_fname)
     flat.store(flat_fname)
 
-def _process_approximate_flat(_project : vstarstack.tool.cfg.Project,
+def _process_approximate_flat(project : vstarstack.tool.cfg.Project,
                               argv : list[str]):
-    input_fname = argv[0]
-    output_fname = argv[1]
+    if len(argv) >= 2:
+        input_fname = argv[0]
+        flat_fname = argv[1]
+    else:
+        input_fname = project.config.paths.flat.result
+        flat_fname = project.config.paths.flat.result
+
     df = vstarstack.library.data.DataFrame.load(input_fname)
     df = vstarstack.library.calibration.flat.approximate_flat_image(df)
-    df.store(output_fname)
+    df.store(flat_fname)
 
 commands = {
     "flatten": (_process_flatten,

src/vstarstack/tool/clean.py

@@ -18,11 +18,10 @@
 import vstarstack.tool.cfg
 
 def run(project: vstarstack.tool.cfg.Project, _argv: list):
-    orig = project.config.paths.npy_orig
-    fixed = project.config.paths.npy_fixed
+    orig = project.config.paths.light.npy
     shifted = project.config.paths.aligned
 
-    for path in [orig, fixed, shifted]:
+    for path in [orig, shifted]:
         files = vstarstack.tool.common.listfiles(path, ".zip")
         for _, filename in files:
             print(filename)

src/vstarstack/tool/config.py

@@ -24,11 +24,22 @@
         "projection" : (str, "COPY"),
     },
     "paths": {
-        "original": (str, "orig", {"directory" : True}),
-        "npy_orig": (str, "npy_orig", {"directory" : True}),
-        "npy_fixed": (str, "npy", {"directory" : True}),
+        "light" : {
+            "original": (str, "orig/light", {"directory" : True}),
+            "npy": (str, "npy/light", {"directory" : True}),
+            "result" : (str, "light.zip"),
+        },
+        "flat" : {
+            "original": (str, "orig/flat", {"directory" : True}),
+            "npy": (str, "npy/flat", {"directory" : True}),
+            "result" : (str, "flat.zip"),
+        },
+        "dark" : {
+            "original": (str, "orig/dark", {"directory" : True}),
+            "npy": (str, "npy/dark", {"directory" : True}),
+            "result" : (str, "dark.zip"),
+        },
         "aligned": (str, "aligned", {"directory" : True}),
-        "output": (str, "sum.zip"),
         "descs" : (str, "descs", {"directory" : True}),
         "relative_shifts": (str, "shifts.json"),
         "absolute_shifts": (str, "shift.json"),

src/vstarstack/tool/decode.py

@@ -81,5 +81,5 @@ def run(project: vstarstack.tool.cfg.Project, argv: list):
             _process_file(input_path, default_format, input_path, output_path)
     else:
         _process_path(default_format,
-                      project.config.paths.npy_orig,
-                      project.config.paths.npy_fixed)
+                      project.config.paths.light.npy,
+                      project.config.paths.light.npy)

src/vstarstack/tool/fine_shift/align_apply.py

@@ -67,7 +67,7 @@ def apply(project: vstarstack.tool.cfg.Project, argv: list):
         else:
             subpixels = 1
     else:
-        npys = project.config.paths.npy_fixed
+        npys = project.config.paths.light.npy
         aligns = project.config.fine_shift.aligns
         subpixels = project.config.fine_shift.subpixels
         outputs = project.config.paths.aligned

src/vstarstack/tool/fine_shift/align_clusters.py

@@ -74,7 +74,7 @@ def align(project: vstarstack.tool.cfg.Project, argv: list):
         cluster_f = argv[1]
         aligns = argv[2]
     else:
-        npys = project.config.paths.npy_fixed
+        npys = project.config.paths.light.npy
         cluster_f = project.config.cluster.path
         aligns = project.config.fine_shift.aligns
 

src/vstarstack/tool/fine_shift/align_correlation.py

@@ -104,7 +104,7 @@ def align(project: vstarstack.tool.cfg.Project, argv: list):
         else:
             pre_aligns = None
     else:
-        npys = project.config.paths.npy_fixed
+        npys = project.config.paths.light.npy
         aligns = project.config.fine_shift.aligns
         pre_aligns = project.config.fine_shift.aligns
 

src/vstarstack/tool/image_processing/blur.py

@@ -54,5 +54,5 @@ def run(project: vstarstack.tool.cfg.Project, argv: list):
         else:
             process_file(argv)
     else:
-        process_dir([project.config.paths.npy_fixed,
-                     project.config.paths.npy_fixed])
+        process_dir([project.config.paths.light.npy,
+                     project.config.paths.light.npy])

src/vstarstack/tool/image_processing/deconvolution.py

@@ -67,8 +67,8 @@ def run(project : vstarstack.tool.cfg.Project, argv : list[str]):
         strength = int(argv[1])
         outputs = argv[2]
     else:
-        inputs = project.config.paths.npy_fixed
-        outputs = project.config.paths.npy_fixed
+        inputs = project.config.paths.light.npy
+        outputs = project.config.paths.light.npy
         strength = int(argv[0])
 
     if os.path.isdir(inputs):

src/vstarstack/tool/image_processing/distorsion.py

@@ -62,5 +62,5 @@ def run(project: vstarstack.tool.cfg.Project, argv: list):
         else:
             _process_file(distorsion, argv)
     else:
-        _process_dir(distorsion, [project.config.paths.npy_fixed,
-                                  project.config.paths.npy_fixed])
+        _process_dir(distorsion, [project.config.paths.light.npy,
+                                  project.config.paths.light.npy])

src/vstarstack/tool/image_processing/fixes.py

@@ -35,8 +35,8 @@ def copy(project: vstarstack.tool.cfg.Project, argv: list):
         orig = argv[0]
         fixed = argv[1]
     else:
-        orig = project.config.paths.npy_orig
-        fixed = project.config.paths.npy_fixed
+        orig = project.config.paths.light.npy
+        fixed = project.config.paths.light.npy
     files = vstarstack.tool.common.listfiles(orig, ".zip")
     for name, fname in files:
         print("Copying ", name)

src/vstarstack/tool/image_processing/normalize.py

@@ -58,8 +58,8 @@ def _process(project: vstarstack.tool.cfg.Project, argv: list):
         else:
             _process_file(argv)
     else:
-        _process_dir([project.config.paths.npy_fixed,
-                      project.config.paths.npy_fixed])
+        _process_dir([project.config.paths.light.npy,
+                      project.config.paths.light.npy])
 
 def run(project: vstarstack.tool.cfg.Project, argv: list):
     _process(project, argv)

src/vstarstack/tool/image_processing/remove_sky.py

@@ -59,8 +59,8 @@ def process(project: vstarstack.tool.cfg.Project, argv: list, model_name : str):
         else:
             process_file(argv, model_name)
     else:
-        process_dir([project.config.paths.npy_fixed,
-                     project.config.paths.npy_fixed], model_name)
+        process_dir([project.config.paths.light.npy,
+                     project.config.paths.light.npy], model_name)
 
 commands = {
     "isoline": (lambda project, argv: process(project, argv, "isoline"),

src/vstarstack/tool/merge.py

@@ -31,7 +31,7 @@ def simple_add(project: vstarstack.tool.cfg.Project, argv: list):
         out = argv[1]
     else:
         path_images = project.config.paths.aligned
-        out = project.config.paths.output
+        out = project.config.paths.light.result
 
     imgs = vstarstack.tool.common.listfiles(path_images, ".zip")
     filenames = [img[1] for img in imgs]
@@ -50,7 +50,7 @@ def sigma_clip(project: vstarstack.tool.cfg.Project, argv: list):
         sigma_steps = 1
     else:
         path_images = project.config.paths.aligned
-        out = project.config.paths.output
+        out = project.config.paths.light.result
         kappa1 = project.config.merge.sigma_clip_coefficient_begin
         kappa2 = project.config.merge.sigma_clip_coefficient_end
         sigma_steps = project.config.merge.sigma_clip_steps

src/vstarstack/tool/objects/cut.py

@@ -22,9 +22,9 @@
 
 def run(project: vstarstack.tool.cfg.Project, argv: list[str]):
     if len(argv) < 3:
-        npypath = project.config.paths.npy_fixed
+        npypath = project.config.paths.light.npy
         jsonpath = project.config.paths.descs
-        cutpath = project.config.paths.npy_fixed
+        cutpath = project.config.paths.light.npy
     else:
         npypath = argv[0]
         jsonpath = argv[1]

src/vstarstack/tool/objects/detect.py

@@ -82,7 +82,7 @@ def _process(project, detector, argv):
             _process_file(project, input_path, output_path, detector)
     else:
         _process_path(project,
-                      project.config.paths.npy_fixed,
+                      project.config.paths.light.npy,
                       project.config.paths.descs,
                       detector)