utils: libtuning: modules: alsc: Add rkisp1 LSC module

Add an LSC module for RkISP1.

Signed-off-by: Paul Elder <[email protected]>
Reviewed-by: Laurent Pinchart <[email protected]>

Author: Rahi374

utils/tuning/libtuning/modules/lsc/__init__.py

@@ -4,3 +4,4 @@
 
 from libtuning.modules.lsc.lsc import LSC
 from libtuning.modules.lsc.raspberrypi import ALSCRaspberryPi
+from libtuning.modules.lsc.rkisp1 import LSCRkISP1

utils/tuning/libtuning/modules/lsc/rkisp1.py

@@ -0,0 +1,112 @@
+# SPDX-License-Identifier: BSD-2-Clause
+#
+# Copyright (C) 2019, Raspberry Pi Ltd
+# Copyright (C) 2022, Paul Elder <[email protected]>
+#
+# rkisp1.py - LSC module for tuning rkisp1
+
+from .lsc import LSC
+
+import libtuning as lt
+import libtuning.utils as utils
+
+from numbers import Number
+import numpy as np
+
+
+class LSCRkISP1(LSC):
+    hr_name = 'LSC (RkISP1)'
+    out_name = 'LensShadingCorrection'
+    # \todo Not sure if this is useful. Probably will remove later.
+    compatible = ['rkisp1']
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(**kwargs)
+
+    # We don't actually need anything from the config file
+    def validate_config(self, config: dict) -> bool:
+        return True
+
+    # @return Image color temperature, flattened array of red calibration table
+    #         (containing {sector size} elements), flattened array of blue
+    #         calibration table, flattened array of (red's) green calibration
+    #         table, flattened array of (blue's) green calibration table
+
+    def _do_single_lsc(self, image: lt.Image):
+        cgr, gr = self._lsc_single_channel(image.channels[lt.Color.GR], image)
+        cgb, gb = self._lsc_single_channel(image.channels[lt.Color.GB], image)
+
+        # \todo Should these ratio against the average of both greens or just
+        # each green like we've done here?
+        cr, _ = self._lsc_single_channel(image.channels[lt.Color.R], image, gr)
+        cb, _ = self._lsc_single_channel(image.channels[lt.Color.B], image, gb)
+
+        return image.color, cr.flatten(), cb.flatten(), cgr.flatten(), cgb.flatten()
+
+    # @return List of dictionaries of color temperature, red table, red's green
+    #         table, blue's green table, and blue table
+
+    def _do_all_lsc(self, images: list) -> list:
+        output_list = []
+        output_map_func = lt.gradient.Linear().map
+
+        # List of colour temperatures
+        list_col = []
+        # Associated calibration tables
+        list_cr = []
+        list_cb = []
+        list_cgr = []
+        list_cgb = []
+        for image in self._enumerate_lsc_images(images):
+            col, cr, cb, cgr, cgb = self._do_single_lsc(image)
+            list_col.append(col)
+            list_cr.append(cr)
+            list_cb.append(cb)
+            list_cgr.append(cgr)
+            list_cgb.append(cgb)
+
+        # Convert to numpy array for data manipulation
+        list_col = np.array(list_col)
+        list_cr = np.array(list_cr)
+        list_cb = np.array(list_cb)
+        list_cgr = np.array(list_cgr)
+        list_cgb = np.array(list_cgb)
+
+        for color_temperature in sorted(set(list_col)):
+            # Average tables for the same colour temperature
+            indices = np.where(list_col == color_temperature)
+            color_temperature = int(color_temperature)
+
+            tables = []
+            for lis in [list_cr, list_cgr, list_cgb, list_cb]:
+                table = np.mean(lis[indices], axis=0)
+                table = output_map_func((1, 3.999), (1024, 4095), table)
+                table = np.round(table).astype('int32').tolist()
+                tables.append(table)
+
+            entry = {
+                'ct': color_temperature,
+                'r': tables[0],
+                'gr': tables[1],
+                'gb': tables[2],
+                'b': tables[3],
+            }
+
+            output_list.append(entry)
+
+        return output_list
+
+    def process(self, config: dict, images: list, outputs: dict) -> dict:
+        output = {}
+
+        # \todo This should actually come from self.sector_{x,y}_gradient
+        size_gradient = lt.gradient.Linear(lt.Remainder.Float)
+        output['x-size'] = size_gradient.distribute(0.5, 8)
+        output['y-size'] = size_gradient.distribute(0.5, 8)
+
+        output['sets'] = self._do_all_lsc(images)
+
+        # \todo Validate images from greyscale camera and force grescale mode
+        # \todo Debug functionality
+
+        return output