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{
    "id": 17654,
    "url": "https://patchwork.libcamera.org/api/1.1/patches/17654/?format=api",
    "web_url": "https://patchwork.libcamera.org/patch/17654/",
    "project": {
        "id": 1,
        "url": "https://patchwork.libcamera.org/api/1.1/projects/1/?format=api",
        "name": "libcamera",
        "link_name": "libcamera",
        "list_id": "libcamera_core",
        "list_email": "libcamera-devel@lists.libcamera.org",
        "web_url": "",
        "scm_url": "",
        "webscm_url": ""
    },
    "msgid": "<20221022062310.2545463-4-paul.elder@ideasonboard.com>",
    "date": "2022-10-22T06:23:02",
    "name": "[libcamera-devel,v2,03/11] utils: libtuning: modules: alsc: Add raspberrypi ALSC module",
    "commit_ref": null,
    "pull_url": null,
    "state": "accepted",
    "archived": false,
    "hash": "1c1952186c423c82fd2d6fbeb5747c79f3961d18",
    "submitter": {
        "id": 17,
        "url": "https://patchwork.libcamera.org/api/1.1/people/17/?format=api",
        "name": "Paul Elder",
        "email": "paul.elder@ideasonboard.com"
    },
    "delegate": null,
    "mbox": "https://patchwork.libcamera.org/patch/17654/mbox/",
    "series": [
        {
            "id": 3573,
            "url": "https://patchwork.libcamera.org/api/1.1/series/3573/?format=api",
            "web_url": "https://patchwork.libcamera.org/project/libcamera/list/?series=3573",
            "date": "2022-10-22T06:22:59",
            "name": "utils: tuning: Add a new tuning infrastructure",
            "version": 2,
            "mbox": "https://patchwork.libcamera.org/series/3573/mbox/"
        }
    ],
    "comments": "https://patchwork.libcamera.org/api/patches/17654/comments/",
    "check": "pending",
    "checks": "https://patchwork.libcamera.org/api/patches/17654/checks/",
    "tags": {},
    "headers": {
        "Return-Path": "<libcamera-devel-bounces@lists.libcamera.org>",
        "X-Original-To": "parsemail@patchwork.libcamera.org",
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        "To": "libcamera-devel@lists.libcamera.org",
        "Date": "Sat, 22 Oct 2022 15:23:02 +0900",
        "Message-Id": "<20221022062310.2545463-4-paul.elder@ideasonboard.com>",
        "X-Mailer": "git-send-email 2.30.2",
        "In-Reply-To": "<20221022062310.2545463-1-paul.elder@ideasonboard.com>",
        "References": "<20221022062310.2545463-1-paul.elder@ideasonboard.com>",
        "MIME-Version": "1.0",
        "Content-Transfer-Encoding": "8bit",
        "Subject": "[libcamera-devel] [PATCH v2 03/11] utils: libtuning: modules: alsc:\n\tAdd raspberrypi ALSC module",
        "X-BeenThere": "libcamera-devel@lists.libcamera.org",
        "X-Mailman-Version": "2.1.29",
        "Precedence": "list",
        "List-Id": "<libcamera-devel.lists.libcamera.org>",
        "List-Unsubscribe": "<https://lists.libcamera.org/options/libcamera-devel>,\n\t<mailto:libcamera-devel-request@lists.libcamera.org?subject=unsubscribe>",
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        "List-Subscribe": "<https://lists.libcamera.org/listinfo/libcamera-devel>,\n\t<mailto:libcamera-devel-request@lists.libcamera.org?subject=subscribe>",
        "From": "Paul Elder via libcamera-devel <libcamera-devel@lists.libcamera.org>",
        "Reply-To": "Paul Elder <paul.elder@ideasonboard.com>",
        "Errors-To": "libcamera-devel-bounces@lists.libcamera.org",
        "Sender": "\"libcamera-devel\" <libcamera-devel-bounces@lists.libcamera.org>"
    },
    "content": "Add an ALSC module for Raspberry Pi.\n\nSigned-off-by: Paul Elder <paul.elder@ideasonboard.com>\n\n---\nNew in v2\n---\n .../tuning/libtuning/modules/alsc/__init__.py |   1 +\n .../libtuning/modules/alsc/raspberrypi.py     | 246 ++++++++++++++++++\n 2 files changed, 247 insertions(+)\n create mode 100644 utils/tuning/libtuning/modules/alsc/raspberrypi.py",
    "diff": "diff --git a/utils/tuning/libtuning/modules/alsc/__init__.py b/utils/tuning/libtuning/modules/alsc/__init__.py\nindex a8f28923..ef6300c2 100644\n--- a/utils/tuning/libtuning/modules/alsc/__init__.py\n+++ b/utils/tuning/libtuning/modules/alsc/__init__.py\n@@ -3,3 +3,4 @@\n # Copyright (C) 2022, Paul Elder <paul.elder@ideasonboard.com>\n \n from libtuning.modules.alsc.alsc import ALSC\n+from libtuning.modules.alsc.raspberrypi import ALSCRaspberryPi\ndiff --git a/utils/tuning/libtuning/modules/alsc/raspberrypi.py b/utils/tuning/libtuning/modules/alsc/raspberrypi.py\nnew file mode 100644\nindex 00000000..bea1a9a9\n--- /dev/null\n+++ b/utils/tuning/libtuning/modules/alsc/raspberrypi.py\n@@ -0,0 +1,246 @@\n+# SPDX-License-Identifier: BSD-2-Clause\n+#\n+# Copyright (C) 2019, Raspberry Pi Ltd\n+# Copyright (C) 2022, Paul Elder <paul.elder@ideasonboard.com>\n+\n+from .alsc import ALSC\n+\n+import libtuning as lt\n+import libtuning.utils as utils\n+\n+from numbers import Number\n+import numpy as np\n+\n+\n+class ALSCRaspberryPi(ALSC):\n+    hr_name = 'ALSC (Raspberry Pi)'\n+    out_name = 'rpi.alsc'\n+    # todo Do something with the compatible list\n+    compatible = ['raspberrypi']\n+\n+    def __init__(self, *,\n+                 do_color: lt.Param,\n+                 luminance_strength: lt.Param,\n+                 **kwargs):\n+        super().__init__(**kwargs)\n+\n+        self.do_color = do_color\n+        self.luminance_strength = luminance_strength\n+\n+        self.output_range = (0, 3.999)\n+\n+    def _validate_config(self, config: dict) -> bool:\n+        if self not in config:\n+            utils.eprint(f'{self.type} not in config')\n+            return False\n+\n+        valid = True\n+\n+        conf = config[self]\n+\n+        lum_key = self.luminance_strength.name\n+        color_key = self.do_color.name\n+\n+        if lum_key not in conf and self.luminance_strength.is_required():\n+            utils.eprint(f'{lum_key} is not in config')\n+            valid = False\n+\n+        if lum_key in conf and (conf[lum_key] < 0 or conf[lum_key] > 1):\n+            utils.eprint(f'Warning: {lum_key} is not in range [0, 1]; defaulting to 0.5')\n+\n+        if color_key not in conf and self.do_color.is_required():\n+            utils.eprint(f'{color_key} is not in config')\n+            valid = False\n+\n+        return valid\n+\n+    # @return Image color temperature, flattened array of red calibration table\n+    #         (containing {sector size} elements), flattened array of blue\n+    #         calibration table, flattened array of green calibration\n+    #         table\n+\n+    def _do_single_alsc(self, image: lt.Image, do_alsc_colour: bool):\n+        average_green = np.mean((image.channels[lt.Color.GR:lt.Color.GB + 1]), axis=0)\n+\n+        cg, g = self._lsc_single_channel(average_green, image)\n+\n+        if not do_alsc_colour:\n+            return image.color, None, None, cg.flatten()\n+\n+        cr, _ = self._lsc_single_channel(image.channels[lt.Color.R], image, g)\n+        cb, _ = self._lsc_single_channel(image.channels[lt.Color.B], image, g)\n+\n+        # todo implement debug\n+\n+        return image.color, cr.flatten(), cb.flatten(), cg.flatten()\n+\n+    # @return Red shading table, Blue shading table, Green shading table,\n+    #         number of images processed\n+\n+    def _do_all_alsc(self, images: list, do_alsc_colour: bool, general_conf: dict) -> (list, list, list, Number, int):\n+        # List of colour temperatures\n+        list_col = []\n+        # Associated calibration tables\n+        list_cr = []\n+        list_cb = []\n+        list_cg = []\n+        count = 0\n+        for image in self._enumerate_alsc_images(images):\n+            col, cr, cb, cg = self._do_single_alsc(image, do_alsc_colour)\n+            list_col.append(col)\n+            list_cr.append(cr)\n+            list_cb.append(cb)\n+            list_cg.append(cg)\n+            count += 1\n+\n+        # Convert to numpy array for data manipulation\n+        list_col = np.array(list_col)\n+        list_cr = np.array(list_cr)\n+        list_cb = np.array(list_cb)\n+        list_cg = np.array(list_cg)\n+\n+        cal_cr_list = []\n+        cal_cb_list = []\n+\n+        # Note: Calculation of average corners and center of the shading tables\n+        # has been removed (which ctt had, as it was being unused)\n+\n+        # todo Handle the second green table\n+\n+        # Average all values for luminance shading and return one table for all temperatures\n+        lum_lut = list(utils.round_with_sigfigs(np.mean(list_cg, axis=0), self.output_range))\n+\n+        if not do_alsc_colour:\n+            return None, None, lum_lut, count\n+\n+        for ct in sorted(set(list_col)):\n+            # Average tables for the same colour temperature\n+            indices = np.where(list_col == ct)\n+            ct = int(ct)\n+            t_r = utils.round_with_sigfigs(np.mean(list_cr[indices], axis=0),\n+                                           self.output_range)\n+            t_b = utils.round_with_sigfigs(np.mean(list_cb[indices], axis=0),\n+                                           self.output_range)\n+\n+            cr_dict = {\n+                'ct': ct,\n+                'table': list(t_r)\n+            }\n+            cb_dict = {\n+                'ct': ct,\n+                'table': list(t_b)\n+            }\n+            cal_cr_list.append(cr_dict)\n+            cal_cb_list.append(cb_dict)\n+\n+        return cal_cr_list, cal_cb_list, lum_lut, count\n+\n+    # @brief Calculate sigma from two adjacent gain tables\n+    def _calcSigma(self, g1, g2):\n+        g1 = np.reshape(g1, self.sector_shape[::-1])\n+        g2 = np.reshape(g2, self.sector_shape[::-1])\n+\n+        # Apply gains to gain table\n+        gg = g1 / g2\n+        if np.mean(gg) < 1:\n+            gg = 1 / gg\n+\n+        # For each internal patch, compute average difference between it and\n+        # its 4 neighbours, then append to list\n+        diffs = []\n+        for i in range(self.sector_shape[1] - 2):\n+            for j in range(self.sector_shape[0] - 2):\n+                # Indexing is incremented by 1 since all patches on borders are\n+                # not counted\n+                diff = np.abs(gg[i + 1][j + 1] - gg[i][j + 1])\n+                diff += np.abs(gg[i + 1][j + 1] - gg[i + 2][j + 1])\n+                diff += np.abs(gg[i + 1][j + 1] - gg[i + 1][j])\n+                diff += np.abs(gg[i + 1][j + 1] - gg[i + 1][j + 2])\n+                diffs.append(diff / 4)\n+\n+        mean_diff = np.mean(diffs)\n+        return(np.round(mean_diff, 5))\n+\n+    # @brief Obtains sigmas for red and blue, effectively a measure of the\n+    # 'error'\n+    def _get_sigma(self, cal_cr_list, cal_cb_list):\n+        # Provided colour alsc tables were generated for two different colour\n+        # temperatures sigma is calculated by comparing two calibration temperatures\n+        # adjacent in colour space\n+\n+        color_temps = [cal['ct'] for cal in cal_cr_list]\n+\n+        # Calculate sigmas for each adjacent color_temps and return worst one\n+        sigma_rs = []\n+        sigma_bs = []\n+        for i in range(len(color_temps) - 1):\n+            sigma_rs.append(self._calcSigma(cal_cr_list[i]['table'], cal_cr_list[i + 1]['table']))\n+            sigma_bs.append(self._calcSigma(cal_cb_list[i]['table'], cal_cb_list[i + 1]['table']))\n+\n+        # Return maximum sigmas, not necessarily from the same colour\n+        # temperature interval\n+        sigma_r = max(sigma_rs) if sigma_rs else 0.005\n+        sigma_b = max(sigma_bs) if sigma_bs else 0.005\n+\n+        return sigma_r, sigma_b\n+\n+    def _process(self, args, config: dict, images: list, outputs: dict) -> dict:\n+        output = {\n+            'omega': 1.3,\n+            'n_iter': 100,\n+            'luminance_strength': 0.7\n+        }\n+\n+        conf = config[self]\n+        general_conf = config['general']\n+\n+        do_alsc_colour = self.do_color.get_value(conf)\n+\n+        # todo I have no idea where this input parameter is used\n+        luminance_strength = self.luminance_strength.get_value(conf)\n+        if luminance_strength < 0 or luminance_strength > 1:\n+            luminance_strength = 0.5\n+\n+        output['luminance_strength'] = luminance_strength\n+\n+        # todo Validate images from greyscale camera and force grescale mode\n+        # todo Debug functionality\n+\n+        alsc_out = self._do_all_alsc(images, do_alsc_colour, general_conf)\n+        # todo Handle the second green lut\n+        cal_cr_list, cal_cb_list, luminance_lut, count = alsc_out\n+\n+        if not do_alsc_colour:\n+            output['luminance_lut'] = luminance_lut\n+            output['n_iter'] = 0\n+            return output\n+\n+        output['calibrations_Cr'] = cal_cr_list\n+        output['calibrations_Cb'] = cal_cb_list\n+        output['luminance_lut'] = luminance_lut\n+\n+        # The sigmas determine the strength of the adaptive algorithm, that\n+        # cleans up any lens shading that has slipped through the alsc. These\n+        # are determined by measuring a 'worst-case' difference between two\n+        # alsc tables that are adjacent in colour space. If, however, only one\n+        # colour temperature has been provided, then this difference can not be\n+        # computed as only one table is available.\n+        # To determine the sigmas you would have to estimate the error of an\n+        # alsc table with only the image it was taken on as a check. To avoid\n+        # circularity, dfault exaggerated sigmas are used, which can result in\n+        # too much alsc and is therefore not advised.\n+        # In general, just take another alsc picture at another colour\n+        # temperature!\n+\n+        if count == 1:\n+            output['sigma'] = 0.005\n+            output['sigma_Cb'] = 0.005\n+            utils.eprint('Warning: Only one alsc calibration found; standard sigmas used for adaptive algorithm.')\n+            return output\n+\n+        # Obtain worst-case scenario residual sigmas\n+        sigma_r, sigma_b = self._get_sigma(cal_cr_list, cal_cb_list)\n+        output['sigma'] = np.round(sigma_r, 5)\n+        output['sigma_Cb'] = np.round(sigma_b, 5)\n+\n+        return output\n",
    "prefixes": [
        "libcamera-devel",
        "v2",
        "03/11"
    ]
}