{"id":20215,"url":"https://patchwork.libcamera.org/api/1.1/patches/20215/?format=json","web_url":"https://patchwork.libcamera.org/patch/20215/","project":{"id":1,"url":"https://patchwork.libcamera.org/api/1.1/projects/1/?format=json","name":"libcamera","link_name":"libcamera","list_id":"libcamera_core","list_email":"libcamera-devel@lists.libcamera.org","web_url":"","scm_url":"","webscm_url":""},"msgid":"<20240606101512.375178-2-david.plowman@raspberrypi.com>","date":"2024-06-06T10:15:07","name":"[1/6] utils: raspberrypi: ctt: Adapt tuning tool for both VC4 and PiSP","commit_ref":null,"pull_url":null,"state":"accepted","archived":false,"hash":"2325450f5c9474b4152197947f31d4765895e287","submitter":{"id":42,"url":"https://patchwork.libcamera.org/api/1.1/people/42/?format=json","name":"David Plowman","email":"david.plowman@raspberrypi.com"},"delegate":null,"mbox":"https://patchwork.libcamera.org/patch/20215/mbox/","series":[{"id":4367,"url":"https://patchwork.libcamera.org/api/1.1/series/4367/?format=json","web_url":"https://patchwork.libcamera.org/project/libcamera/list/?series=4367","date":"2024-06-06T10:15:06","name":"Raspberry Pi Camera Tuning Tool updates","version":1,"mbox":"https://patchwork.libcamera.org/series/4367/mbox/"}],"comments":"https://patchwork.libcamera.org/api/patches/20215/comments/","check":"pending","checks":"https://patchwork.libcamera.org/api/patches/20215/checks/","tags":{},"headers":{"Return-Path":"","X-Original-To":"parsemail@patchwork.libcamera.org","Delivered-To":"parsemail@patchwork.libcamera.org","Received":["from lancelot.ideasonboard.com (lancelot.ideasonboard.com\n\t[92.243.16.209])\n\tby patchwork.libcamera.org (Postfix) with ESMTPS id C347FBD87C\n\tfor ;\n\tThu, 6 Jun 2024 10:15:35 +0000 (UTC)","from lancelot.ideasonboard.com (localhost [IPv6:::1])\n\tby lancelot.ideasonboard.com (Postfix) with ESMTP id 6C88565463;\n\tThu, 6 Jun 2024 12:15:35 +0200 (CEST)","from mail-ej1-x635.google.com (mail-ej1-x635.google.com\n\t[IPv6:2a00:1450:4864:20::635])\n\tby lancelot.ideasonboard.com (Postfix) with ESMTPS id 626CA634D5\n\tfor ;\n\tThu, 6 Jun 2024 12:15:31 +0200 (CEST)","by mail-ej1-x635.google.com with SMTP id\n\ta640c23a62f3a-a69607c6ccaso78531466b.2\n\tfor ;\n\tThu, 06 Jun 2024 03:15:31 -0700 (PDT)","from pi5-davidp.pitowers.org\n\t([2001:4d4e:300:1f:c732:5d0a:406b:ae46])\n\tby smtp.gmail.com with ESMTPSA id\n\ta640c23a62f3a-a6c805c59a2sm75809866b.50.2024.06.06.03.15.27\n\t(version=TLS1_3 cipher=TLS_AES_256_GCM_SHA384 bits=256/256);\n\tThu, 06 Jun 2024 03:15:28 -0700 (PDT)"],"Authentication-Results":"lancelot.ideasonboard.com; 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\n\tThu, 06 Jun 2024 03:15:29 -0700 (PDT)","From":"David Plowman ","To":"libcamera-devel@lists.libcamera.org","Cc":"David Plowman ,\n\tNaushir Patuck ","Subject":"[PATCH 1/6] utils: raspberrypi: ctt: Adapt tuning tool for both VC4\n\tand PiSP","Date":"Thu, 6 Jun 2024 11:15:07 +0100","Message-Id":"<20240606101512.375178-2-david.plowman@raspberrypi.com>","X-Mailer":"git-send-email 2.39.2","In-Reply-To":"<20240606101512.375178-1-david.plowman@raspberrypi.com>","References":"<20240606101512.375178-1-david.plowman@raspberrypi.com>","MIME-Version":"1.0","Content-Transfer-Encoding":"8bit","X-BeenThere":"libcamera-devel@lists.libcamera.org","X-Mailman-Version":"2.1.29","Precedence":"list","List-Id":"","List-Unsubscribe":",\n\t","List-Archive":"","List-Post":"","List-Help":"","List-Subscribe":",\n\t","Errors-To":"libcamera-devel-bounces@lists.libcamera.org","Sender":"\"libcamera-devel\" "},"content":"The old ctt.py and alsc_only.py scripts are removed.\n\nInstead of ctt.py use ctt_vc4.py or ctt_pisp.py, depending on your\ntarget platform.\n\nInstead of alsc_only.py use alsc_vc4.py or alsc_pisp.py, again\naccording to your platform.\n\nSigned-off-by: David Plowman \nReviewed-by: Naushir Patuck \n---\n utils/raspberrypi/ctt/alsc_pisp.py | 37 +++\n .../ctt/{alsc_only.py => alsc_vc4.py} | 9 +-\n utils/raspberrypi/ctt/ctt_alsc.py | 75 +++---\n utils/raspberrypi/ctt/ctt_awb.py | 11 +-\n utils/raspberrypi/ctt/ctt_ccm.py | 6 +-\n utils/raspberrypi/ctt/ctt_pisp.py | 233 ++++++++++++++++++\n .../raspberrypi/ctt/ctt_pretty_print_json.py | 7 +-\n utils/raspberrypi/ctt/{ctt.py => ctt_run.py} | 184 ++------------\n utils/raspberrypi/ctt/ctt_vc4.py | 157 ++++++++++++\n 9 files changed, 511 insertions(+), 208 deletions(-)\n create mode 100755 utils/raspberrypi/ctt/alsc_pisp.py\n rename utils/raspberrypi/ctt/{alsc_only.py => alsc_vc4.py} (70%)\n create mode 100755 utils/raspberrypi/ctt/ctt_pisp.py\n rename utils/raspberrypi/ctt/{ctt.py => ctt_run.py} (82%)\n create mode 100755 utils/raspberrypi/ctt/ctt_vc4.py","diff":"diff --git a/utils/raspberrypi/ctt/alsc_pisp.py b/utils/raspberrypi/ctt/alsc_pisp.py\nnew file mode 100755\nindex 00000000..499aecd1\n--- /dev/null\n+++ b/utils/raspberrypi/ctt/alsc_pisp.py\n@@ -0,0 +1,37 @@\n+#!/usr/bin/env python3\n+#\n+# SPDX-License-Identifier: BSD-2-Clause\n+#\n+# Copyright (C) 2022, Raspberry Pi (Trading) Limited\n+#\n+# alsc_only.py - alsc tuning tool\n+\n+import sys\n+\n+from ctt_pisp import json_template, grid_size, target\n+from ctt_run import run_ctt\n+from ctt_tools import parse_input\n+\n+if __name__ == '__main__':\n+ \"\"\"\n+ initialise calibration\n+ \"\"\"\n+ if len(sys.argv) == 1:\n+ print(\"\"\"\n+ PiSP Lens Shading Camera Tuning Tool version 1.0\n+\n+ Required Arguments:\n+ '-i' : Calibration image directory.\n+ '-o' : Name of output json file.\n+\n+ Optional Arguments:\n+ '-c' : Config file for the CTT. If not passed, default parameters used.\n+ '-l' : Name of output log file. If not passed, 'ctt_log.txt' used.\n+ \"\"\")\n+ quit(0)\n+ else:\n+ \"\"\"\n+ parse input arguments\n+ \"\"\"\n+ json_output, directory, config, log_output = parse_input()\n+ run_ctt(json_output, directory, config, log_output, json_template, grid_size, target, alsc_only=True)\ndiff --git a/utils/raspberrypi/ctt/alsc_only.py b/utils/raspberrypi/ctt/alsc_vc4.py\nsimilarity index 70%\nrename from utils/raspberrypi/ctt/alsc_only.py\nrename to utils/raspberrypi/ctt/alsc_vc4.py\nindex 092aa40e..caf6a174 100755\n--- a/utils/raspberrypi/ctt/alsc_only.py\n+++ b/utils/raspberrypi/ctt/alsc_vc4.py\n@@ -6,8 +6,11 @@\n #\n # alsc tuning tool\n \n-from ctt import *\n+import sys\n \n+from ctt_vc4 import json_template, grid_size, target\n+from ctt_run import run_ctt\n+from ctt_tools import parse_input\n \n if __name__ == '__main__':\n \"\"\"\n@@ -15,7 +18,7 @@ if __name__ == '__main__':\n \"\"\"\n if len(sys.argv) == 1:\n print(\"\"\"\n- Pisp Camera Tuning Tool version 1.0\n+ VC4 Lens Shading Camera Tuning Tool version 1.0\n \n Required Arguments:\n '-i' : Calibration image directory.\n@@ -31,4 +34,4 @@ if __name__ == '__main__':\n parse input arguments\n \"\"\"\n json_output, directory, config, log_output = parse_input()\n- run_ctt(json_output, directory, config, log_output, alsc_only=True)\n+ run_ctt(json_output, directory, config, log_output, json_template, grid_size, target, alsc_only=True)\ndiff --git a/utils/raspberrypi/ctt/ctt_alsc.py b/utils/raspberrypi/ctt/ctt_alsc.py\nindex b0201ac4..66ce8c14 100644\n--- a/utils/raspberrypi/ctt/ctt_alsc.py\n+++ b/utils/raspberrypi/ctt/ctt_alsc.py\n@@ -13,8 +13,9 @@ from mpl_toolkits.mplot3d import Axes3D\n \"\"\"\n preform alsc calibration on a set of images\n \"\"\"\n-def alsc_all(Cam, do_alsc_colour, plot):\n+def alsc_all(Cam, do_alsc_colour, plot, grid_size=(16, 12)):\n imgs_alsc = Cam.imgs_alsc\n+ grid_w, grid_h = grid_size\n \"\"\"\n create list of colour temperatures and associated calibration tables\n \"\"\"\n@@ -23,7 +24,7 @@ def alsc_all(Cam, do_alsc_colour, plot):\n list_cb = []\n list_cg = []\n for Img in imgs_alsc:\n- col, cr, cb, cg, size = alsc(Cam, Img, do_alsc_colour, plot)\n+ col, cr, cb, cg, size = alsc(Cam, Img, do_alsc_colour, plot, grid_size=grid_size)\n list_col.append(col)\n list_cr.append(cr)\n list_cb.append(cb)\n@@ -68,11 +69,12 @@ def alsc_all(Cam, do_alsc_colour, plot):\n t_b = np.where((100*t_b) % 1 >= 0.95, t_b-0.001, t_b)\n t_r = np.round(t_r, 3)\n t_b = np.round(t_b, 3)\n- r_corners = (t_r[0], t_r[15], t_r[-1], t_r[-16])\n- b_corners = (t_b[0], t_b[15], t_b[-1], t_b[-16])\n- r_cen = t_r[5*16+7]+t_r[5*16+8]+t_r[6*16+7]+t_r[6*16+8]\n+ r_corners = (t_r[0], t_r[grid_w - 1], t_r[-1], t_r[-grid_w])\n+ b_corners = (t_b[0], t_b[grid_w - 1], t_b[-1], t_b[-grid_w])\n+ middle_pos = (grid_h // 2 - 1) * grid_w + grid_w - 1\n+ r_cen = t_r[middle_pos]+t_r[middle_pos + 1]+t_r[middle_pos + grid_w]+t_r[middle_pos + grid_w + 1]\n r_cen = round(r_cen/4, 3)\n- b_cen = t_b[5*16+7]+t_b[5*16+8]+t_b[6*16+7]+t_b[6*16+8]\n+ b_cen = t_b[middle_pos]+t_b[middle_pos + 1]+t_b[middle_pos + grid_w]+t_b[middle_pos + grid_w + 1]\n b_cen = round(b_cen/4, 3)\n Cam.log += '\\nRed table corners: {}'.format(r_corners)\n Cam.log += '\\nRed table centre: {}'.format(r_cen)\n@@ -116,8 +118,9 @@ def alsc_all(Cam, do_alsc_colour, plot):\n \"\"\"\n calculate g/r and g/b for 32x32 points arranged in a grid for a single image\n \"\"\"\n-def alsc(Cam, Img, do_alsc_colour, plot=False):\n+def alsc(Cam, Img, do_alsc_colour, plot=False, grid_size=(16, 12)):\n Cam.log += '\\nProcessing image: ' + Img.name\n+ grid_w, grid_h = grid_size\n \"\"\"\n get channel in correct order\n \"\"\"\n@@ -128,24 +131,24 @@ def alsc(Cam, Img, do_alsc_colour, plot=False):\n where w is a multiple of 32.\n \"\"\"\n w, h = Img.w/2, Img.h/2\n- dx, dy = int(-(-(w-1)//16)), int(-(-(h-1)//12))\n+ dx, dy = int(-(-(w-1)//grid_w)), int(-(-(h-1)//grid_h))\n \"\"\"\n average the green channels into one\n \"\"\"\n av_ch_g = np.mean((channels[1:3]), axis=0)\n if do_alsc_colour:\n \"\"\"\n- obtain 16x12 grid of intensities for each channel and subtract black level\n+ obtain grid_w x grid_h grid of intensities for each channel and subtract black level\n \"\"\"\n- g = get_16x12_grid(av_ch_g, dx, dy) - Img.blacklevel_16\n- r = get_16x12_grid(channels[0], dx, dy) - Img.blacklevel_16\n- b = get_16x12_grid(channels[3], dx, dy) - Img.blacklevel_16\n+ g = get_grid(av_ch_g, dx, dy, grid_size) - Img.blacklevel_16\n+ r = get_grid(channels[0], dx, dy, grid_size) - Img.blacklevel_16\n+ b = get_grid(channels[3], dx, dy, grid_size) - Img.blacklevel_16\n \"\"\"\n calculate ratios as 32 bit in order to be supported by medianBlur function\n \"\"\"\n- cr = np.reshape(g/r, (12, 16)).astype('float32')\n- cb = np.reshape(g/b, (12, 16)).astype('float32')\n- cg = np.reshape(1/g, (12, 16)).astype('float32')\n+ cr = np.reshape(g/r, (grid_h, grid_w)).astype('float32')\n+ cb = np.reshape(g/b, (grid_h, grid_w)).astype('float32')\n+ cg = np.reshape(1/g, (grid_h, grid_w)).astype('float32')\n \"\"\"\n median blur to remove peaks and save as float 64\n \"\"\"\n@@ -164,7 +167,7 @@ def alsc(Cam, Img, do_alsc_colour, plot=False):\n \"\"\"\n note Y is plotted as -Y so plot has same axes as image\n \"\"\"\n- X, Y = np.meshgrid(range(16), range(12))\n+ X, Y = np.meshgrid(range(grid_w), range(grid_h))\n ha.plot_surface(X, -Y, cr, cmap=cm.coolwarm, linewidth=0)\n ha.set_title('ALSC Plot\\nImg: {}\\n\\ncr'.format(Img.str))\n hb = hf.add_subplot(312, projection='3d')\n@@ -182,15 +185,15 @@ def alsc(Cam, Img, do_alsc_colour, plot=False):\n \"\"\"\n only perform calculations for luminance shading\n \"\"\"\n- g = get_16x12_grid(av_ch_g, dx, dy) - Img.blacklevel_16\n- cg = np.reshape(1/g, (12, 16)).astype('float32')\n+ g = get_grid(av_ch_g, dx, dy, grid_size) - Img.blacklevel_16\n+ cg = np.reshape(1/g, (grid_h, grid_w)).astype('float32')\n cg = cv2.medianBlur(cg, 3).astype('float64')\n cg = cg/np.min(cg)\n \n if plot:\n hf = plt.figure(figssize=(8, 8))\n ha = hf.add_subplot(1, 1, 1, projection='3d')\n- X, Y = np.meashgrid(range(16), range(12))\n+ X, Y = np.meashgrid(range(grid_w), range(grid_h))\n ha.plot_surface(X, -Y, cg, cmap=cm.coolwarm, linewidth=0)\n ha.set_title('ALSC Plot (Luminance only!)\\nImg: {}\\n\\ncg').format(Img.str)\n plt.show()\n@@ -199,21 +202,22 @@ def alsc(Cam, Img, do_alsc_colour, plot=False):\n \n \n \"\"\"\n-Compresses channel down to a 16x12 grid\n+Compresses channel down to a grid of the requested size\n \"\"\"\n-def get_16x12_grid(chan, dx, dy):\n+def get_grid(chan, dx, dy, grid_size):\n+ grid_w, grid_h = grid_size\n grid = []\n \"\"\"\n since left and bottom border will not necessarily have rectangles of\n dimension dx x dy, the 32nd iteration has to be handled separately.\n \"\"\"\n- for i in range(11):\n- for j in range(15):\n+ for i in range(grid_h - 1):\n+ for j in range(grid_w - 1):\n grid.append(np.mean(chan[dy*i:dy*(1+i), dx*j:dx*(1+j)]))\n- grid.append(np.mean(chan[dy*i:dy*(1+i), 15*dx:]))\n- for j in range(15):\n- grid.append(np.mean(chan[11*dy:, dx*j:dx*(1+j)]))\n- grid.append(np.mean(chan[11*dy:, 15*dx:]))\n+ grid.append(np.mean(chan[dy*i:dy*(1+i), (grid_w - 1)*dx:]))\n+ for j in range(grid_w - 1):\n+ grid.append(np.mean(chan[(grid_h - 1)*dy:, dx*j:dx*(1+j)]))\n+ grid.append(np.mean(chan[(grid_h - 1)*dy:, (grid_w - 1)*dx:]))\n \"\"\"\n return as np.array, ready for further manipulation\n \"\"\"\n@@ -223,7 +227,7 @@ def get_16x12_grid(chan, dx, dy):\n \"\"\"\n obtains sigmas for red and blue, effectively a measure of the 'error'\n \"\"\"\n-def get_sigma(Cam, cal_cr_list, cal_cb_list):\n+def get_sigma(Cam, cal_cr_list, cal_cb_list, grid_size):\n Cam.log += '\\nCalculating sigmas'\n \"\"\"\n provided colour alsc tables were generated for two different colour\n@@ -241,8 +245,8 @@ def get_sigma(Cam, cal_cr_list, cal_cb_list):\n sigma_rs = []\n sigma_bs = []\n for i in range(len(cts)-1):\n- sigma_rs.append(calc_sigma(cal_cr_list[i]['table'], cal_cr_list[i+1]['table']))\n- sigma_bs.append(calc_sigma(cal_cb_list[i]['table'], cal_cb_list[i+1]['table']))\n+ sigma_rs.append(calc_sigma(cal_cr_list[i]['table'], cal_cr_list[i+1]['table'], grid_size))\n+ sigma_bs.append(calc_sigma(cal_cb_list[i]['table'], cal_cb_list[i+1]['table'], grid_size))\n Cam.log += '\\nColour temperature interval {} - {} K'.format(cts[i], cts[i+1])\n Cam.log += '\\nSigma red: {}'.format(sigma_rs[-1])\n Cam.log += '\\nSigma blue: {}'.format(sigma_bs[-1])\n@@ -263,12 +267,13 @@ def get_sigma(Cam, cal_cr_list, cal_cb_list):\n \"\"\"\n calculate sigma from two adjacent gain tables\n \"\"\"\n-def calc_sigma(g1, g2):\n+def calc_sigma(g1, g2, grid_size):\n+ grid_w, grid_h = grid_size\n \"\"\"\n reshape into 16x12 matrix\n \"\"\"\n- g1 = np.reshape(g1, (12, 16))\n- g2 = np.reshape(g2, (12, 16))\n+ g1 = np.reshape(g1, (grid_h, grid_w))\n+ g2 = np.reshape(g2, (grid_h, grid_w))\n \"\"\"\n apply gains to gain table\n \"\"\"\n@@ -280,8 +285,8 @@ def calc_sigma(g1, g2):\n neighbours, then append to list\n \"\"\"\n diffs = []\n- for i in range(10):\n- for j in range(14):\n+ for i in range(grid_h - 2):\n+ for j in range(grid_w - 2):\n \"\"\"\n note indexing is incremented by 1 since all patches on borders are\n not counted\ndiff --git a/utils/raspberrypi/ctt/ctt_awb.py b/utils/raspberrypi/ctt/ctt_awb.py\nindex 5ba6f978..4af1fe41 100644\n--- a/utils/raspberrypi/ctt/ctt_awb.py\n+++ b/utils/raspberrypi/ctt/ctt_awb.py\n@@ -13,7 +13,7 @@ from scipy.optimize import fmin\n \"\"\"\n obtain piecewise linear approximation for colour curve\n \"\"\"\n-def awb(Cam, cal_cr_list, cal_cb_list, plot):\n+def awb(Cam, cal_cr_list, cal_cb_list, plot, grid_size):\n imgs = Cam.imgs\n \"\"\"\n condense alsc calibration tables into one dictionary\n@@ -43,7 +43,7 @@ def awb(Cam, cal_cr_list, cal_cb_list, plot):\n Note: if alsc is disabled then colour_cals will be set to None and the\n function will just return the greyscale patches\n \"\"\"\n- r_patchs, b_patchs, g_patchs = get_alsc_patches(Img, colour_cals)\n+ r_patchs, b_patchs, g_patchs = get_alsc_patches(Img, colour_cals, grid_size=grid_size)\n \"\"\"\n calculate ratio of r, b to g\n \"\"\"\n@@ -293,12 +293,13 @@ def awb(Cam, cal_cr_list, cal_cb_list, plot):\n \"\"\"\n obtain greyscale patches and perform alsc colour correction\n \"\"\"\n-def get_alsc_patches(Img, colour_cals, grey=True):\n+def get_alsc_patches(Img, colour_cals, grey=True, grid_size=(16, 12)):\n \"\"\"\n get patch centre coordinates, image colour and the actual\n patches for each channel, remembering to subtract blacklevel\n If grey then only greyscale patches considered\n \"\"\"\n+ grid_w, grid_h = grid_size\n if grey:\n cen_coords = Img.cen_coords[3::4]\n col = Img.col\n@@ -345,12 +346,12 @@ def get_alsc_patches(Img, colour_cals, grey=True):\n bef_tabs = np.array(colour_cals[bef])\n aft_tabs = np.array(colour_cals[aft])\n col_tabs = (bef_tabs*db + aft_tabs*da)/(da+db)\n- col_tabs = np.reshape(col_tabs, (2, 12, 16))\n+ col_tabs = np.reshape(col_tabs, (2, grid_h, grid_w))\n \"\"\"\n calculate dx, dy used to calculate alsc table\n \"\"\"\n w, h = Img.w/2, Img.h/2\n- dx, dy = int(-(-(w-1)//16)), int(-(-(h-1)//12))\n+ dx, dy = int(-(-(w-1)//grid_w)), int(-(-(h-1)//grid_h))\n \"\"\"\n make list of pairs of gains for each patch by selecting the correct value\n in alsc colour calibration table\ndiff --git a/utils/raspberrypi/ctt/ctt_ccm.py b/utils/raspberrypi/ctt/ctt_ccm.py\nindex 59753e33..07c943a8 100644\n--- a/utils/raspberrypi/ctt/ctt_ccm.py\n+++ b/utils/raspberrypi/ctt/ctt_ccm.py\n@@ -56,7 +56,7 @@ FInds colour correction matrices for list of images\n \"\"\"\n \n \n-def ccm(Cam, cal_cr_list, cal_cb_list):\n+def ccm(Cam, cal_cr_list, cal_cb_list, grid_size):\n global matrix_selection_types, typenum\n imgs = Cam.imgs\n \"\"\"\n@@ -133,9 +133,7 @@ def ccm(Cam, cal_cr_list, cal_cb_list):\n Note: if alsc is disabled then colour_cals will be set to None and no\n the function will simply return the macbeth patches\n \"\"\"\n- r, b, g = get_alsc_patches(Img, colour_cals, grey=False)\n- # 256 values for each patch of sRGB values\n-\n+ r, b, g = get_alsc_patches(Img, colour_cals, grey=False, grid_size=grid_size)\n \"\"\"\n do awb\n Note: awb is done by measuring the macbeth chart in the image, rather\ndiff --git a/utils/raspberrypi/ctt/ctt_pisp.py b/utils/raspberrypi/ctt/ctt_pisp.py\nnew file mode 100755\nindex 00000000..f837e062\n--- /dev/null\n+++ b/utils/raspberrypi/ctt/ctt_pisp.py\n@@ -0,0 +1,233 @@\n+#!/usr/bin/env python3\n+#\n+# SPDX-License-Identifier: BSD-2-Clause\n+#\n+# Copyright (C) 2019, Raspberry Pi Ltd\n+#\n+# ctt_pisp.py - camera tuning tool for PiSP platforms\n+\n+import os\n+import sys\n+\n+from ctt_run import run_ctt\n+from ctt_tools import parse_input\n+\n+json_template = {\n+ \"rpi.black_level\": {\n+ \"black_level\": 4096\n+ },\n+ \"rpi.lux\": {\n+ \"reference_shutter_speed\": 10000,\n+ \"reference_gain\": 1,\n+ \"reference_aperture\": 1.0\n+ },\n+ \"rpi.dpc\": {\n+\t\"strength\": 1\n+ },\n+ \"rpi.noise\": {\n+ },\n+ \"rpi.geq\": {\n+ },\n+ \"rpi.denoise\":\n+ {\n+ \"sdn\":\n+ {\n+ \"deviation\": 1.6,\n+ \"strength\": 0.5,\n+ \"deviation2\": 3.2,\n+ \"deviation_no_tdn\": 3.2,\n+ \"strength_no_tdn\": 0.75\n+ },\n+ \"cdn\":\n+ {\n+ \"deviation\": 200,\n+ \"strength\": 0.3\n+ },\n+ \"tdn\":\n+ {\n+ \"deviation\": 0.8,\n+ \"threshold\": 0.05\n+ }\n+ },\n+ \"rpi.awb\": {\n+ \"priors\": [\n+ {\"lux\": 0, \"prior\": [2000, 1.0, 3000, 0.0, 13000, 0.0]},\n+ {\"lux\": 800, \"prior\": [2000, 0.0, 6000, 2.0, 13000, 2.0]},\n+ {\"lux\": 1500, \"prior\": [2000, 0.0, 4000, 1.0, 6000, 6.0, 6500, 7.0, 7000, 1.0, 13000, 1.0]}\n+ ],\n+ \"modes\": {\n+ \"auto\": {\"lo\": 2500, \"hi\": 7700},\n+ \"incandescent\": {\"lo\": 2500, \"hi\": 3000},\n+ \"tungsten\": {\"lo\": 3000, \"hi\": 3500},\n+ \"fluorescent\": {\"lo\": 4000, \"hi\": 4700},\n+ \"indoor\": {\"lo\": 3000, \"hi\": 5000},\n+ \"daylight\": {\"lo\": 5500, \"hi\": 6500},\n+ \"cloudy\": {\"lo\": 7000, \"hi\": 8000}\n+ },\n+ \"bayes\": 1\n+ },\n+ \"rpi.agc\": {\n+ \"metering_modes\": {\n+ \"centre-weighted\": {\n+\t\t\"weights\": [\n+\t\t 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0,\n+\t\t 0, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 0,\n+\t\t 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1,\n+\t\t 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1,\n+\t\t 1, 1, 2, 2, 2, 2, 3, 3, 3, 2, 2, 2, 2, 1, 1,\n+\t\t 1, 1, 2, 2, 2, 3, 3, 3, 3, 3, 2, 2, 2, 1, 1,\n+\t\t 1, 1, 2, 2, 3, 3, 3, 4, 3, 3, 3, 2, 2, 1, 1,\n+\t\t 1, 1, 2, 2, 3, 3, 4, 4, 4, 3, 3, 2, 2, 1, 1,\n+\t\t 1, 1, 2, 2, 3, 3, 3, 4, 3, 3, 3, 2, 2, 1, 1,\n+\t\t 1, 1, 2, 2, 2, 3, 3, 3, 3, 3, 2, 2, 2, 1, 1,\n+\t\t 1, 1, 2, 2, 2, 2, 3, 3, 3, 2, 2, 2, 2, 1, 1,\n+\t\t 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1,\n+\t\t 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1,\n+\t\t 0, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 0,\n+\t\t 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0\n+\t\t]\n+ },\n+ \"spot\": {\n+\t\t\"weights\": [\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 1, 2, 1, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 1, 2, 3, 2, 1, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 1, 2, 1, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n+\t\t 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0\n+\t\t]\n+ },\n+ \"matrix\": {\n+ \"weights\": [\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n+\t\t 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1\n+\t\t]\n+ }\n+ },\n+ \"exposure_modes\": {\n+ \"normal\": {\n+ \"shutter\": [100, 10000, 30000, 60000, 66666],\n+ \"gain\": [1.0, 1.5, 2.0, 4.0, 8.0]\n+ },\n+ \"short\": {\n+ \"shutter\": [100, 5000, 10000, 20000, 60000],\n+ \"gain\": [1.0, 1.5, 2.0, 4.0, 8.0]\n+ },\n+ \"long\":\n+ {\n+ \"shutter\": [ 100, 10000, 30000, 60000, 90000, 120000 ],\n+ \"gain\": [ 1.0, 1.5, 2.0, 4.0, 8.0, 12.0 ]\n+ }\n+ },\n+ \"constraint_modes\": {\n+ \"normal\": [\n+ {\"bound\": \"LOWER\", \"q_lo\": 0.98, \"q_hi\": 1.0, \"y_target\": [0, 0.5, 1000, 0.5]}\n+ ],\n+ \"highlight\": [\n+ {\"bound\": \"LOWER\", \"q_lo\": 0.98, \"q_hi\": 1.0, \"y_target\": [0, 0.5, 1000, 0.5]},\n+ {\"bound\": \"UPPER\", \"q_lo\": 0.98, \"q_hi\": 1.0, \"y_target\": [0, 0.8, 1000, 0.8]}\n+ ]\n+ },\n+ \"y_target\": [0, 0.16, 1000, 0.165, 10000, 0.17]\n+ },\n+ \"rpi.alsc\": {\n+ 'omega': 1.3,\n+ 'n_iter': 100,\n+ 'luminance_strength': 0.8,\n+ },\n+ \"rpi.contrast\": {\n+ \"ce_enable\": 1,\n+ \"gamma_curve\": [\n+ 0, 0,\n+ 1024, 5040,\n+ 2048, 9338,\n+ 3072, 12356,\n+ 4096, 15312,\n+ 5120, 18051,\n+ 6144, 20790,\n+ 7168, 23193,\n+ 8192, 25744,\n+ 9216, 27942,\n+ 10240, 30035,\n+ 11264, 32005,\n+ 12288, 33975,\n+ 13312, 35815,\n+ 14336, 37600,\n+ 15360, 39168,\n+ 16384, 40642,\n+ 18432, 43379,\n+ 20480, 45749,\n+ 22528, 47753,\n+ 24576, 49621,\n+ 26624, 51253,\n+ 28672, 52698,\n+ 30720, 53796,\n+ 32768, 54876,\n+ 36864, 57012,\n+ 40960, 58656,\n+ 45056, 59954,\n+ 49152, 61183,\n+ 53248, 62355,\n+ 57344, 63419,\n+ 61440, 64476,\n+ 65535, 65535\n+ ]\n+ },\n+ \"rpi.ccm\": {\n+ },\n+ \"rpi.sharpen\": {\n+\t\"threshold\": 0.25,\n+\t\"limit\": 1.0,\n+\t\"strength\": 1.0\n+ }\n+}\n+\n+grid_size = (32, 32)\n+\n+target = 'pisp'\n+\n+if __name__ == '__main__':\n+ \"\"\"\n+ initialise calibration\n+ \"\"\"\n+ if len(sys.argv) == 1:\n+ print(\"\"\"\n+ PiSP Camera Tuning Tool version 1.0\n+\n+ Required Arguments:\n+ '-i' : Calibration image directory.\n+ '-o' : Name of output json file.\n+\n+ Optional Arguments:\n+ '-c' : Config file for the CTT. If not passed, default parameters used.\n+ '-l' : Name of output log file. If not passed, 'ctt_log.txt' used.\n+ \"\"\")\n+ quit(0)\n+ else:\n+ \"\"\"\n+ parse input arguments\n+ \"\"\"\n+ json_output, directory, config, log_output = parse_input()\n+ run_ctt(json_output, directory, config, log_output, json_template, grid_size, target)\ndiff --git a/utils/raspberrypi/ctt/ctt_pretty_print_json.py b/utils/raspberrypi/ctt/ctt_pretty_print_json.py\nindex 3e3b8475..5d16b2a6 100755\n--- a/utils/raspberrypi/ctt/ctt_pretty_print_json.py\n+++ b/utils/raspberrypi/ctt/ctt_pretty_print_json.py\n@@ -19,6 +19,7 @@ class Encoder(json.JSONEncoder):\n self.indentation_level = 0\n self.hard_break = 120\n self.custom_elems = {\n+ 'weights': 15,\n 'table': 16,\n 'luminance_lut': 16,\n 'ct_curve': 3,\n@@ -87,7 +88,7 @@ class Encoder(json.JSONEncoder):\n return self.encode(o)\n \n \n-def pretty_print(in_json: dict) -> str:\n+def pretty_print(in_json: dict, custom_elems={}) -> str:\n \n if 'version' not in in_json or \\\n 'target' not in in_json or \\\n@@ -95,7 +96,9 @@ def pretty_print(in_json: dict) -> str:\n in_json['version'] < 2.0:\n raise RuntimeError('Incompatible JSON dictionary has been provided')\n \n- return json.dumps(in_json, cls=Encoder, indent=4, sort_keys=False)\n+ encoder = Encoder(indent=4, sort_keys=False)\n+ encoder.custom_elems |= custom_elems\n+ return encoder.encode(in_json) #json.dumps(in_json, cls=Encoder, indent=4, sort_keys=False)\n \n \n if __name__ == \"__main__\":\ndiff --git a/utils/raspberrypi/ctt/ctt.py b/utils/raspberrypi/ctt/ctt_run.py\nsimilarity index 82%\nrename from utils/raspberrypi/ctt/ctt.py\nrename to utils/raspberrypi/ctt/ctt_run.py\nindex bbe960b0..0c85d7db 100755\n--- a/utils/raspberrypi/ctt/ctt.py\n+++ b/utils/raspberrypi/ctt/ctt_run.py\n@@ -67,7 +67,7 @@ Camera object that is the backbone of the tuning tool.\n Input is the desired path of the output json.\n \"\"\"\n class Camera:\n- def __init__(self, jfile):\n+ def __init__(self, jfile, json):\n self.path = os.path.dirname(os.path.expanduser(__file__)) + '/'\n if self.path == '/':\n self.path = ''\n@@ -79,127 +79,15 @@ class Camera:\n \"\"\"\n initial json dict populated by uncalibrated values\n \"\"\"\n- self.json = {\n- \"rpi.black_level\": {\n- \"black_level\": 4096\n- },\n- \"rpi.dpc\": {\n- },\n- \"rpi.lux\": {\n- \"reference_shutter_speed\": 10000,\n- \"reference_gain\": 1,\n- \"reference_aperture\": 1.0\n- },\n- \"rpi.noise\": {\n- },\n- \"rpi.geq\": {\n- },\n- \"rpi.sdn\": {\n- },\n- \"rpi.awb\": {\n- \"priors\": [\n- {\"lux\": 0, \"prior\": [2000, 1.0, 3000, 0.0, 13000, 0.0]},\n- {\"lux\": 800, \"prior\": [2000, 0.0, 6000, 2.0, 13000, 2.0]},\n- {\"lux\": 1500, \"prior\": [2000, 0.0, 4000, 1.0, 6000, 6.0, 6500, 7.0, 7000, 1.0, 13000, 1.0]}\n- ],\n- \"modes\": {\n- \"auto\": {\"lo\": 2500, \"hi\": 8000},\n- \"incandescent\": {\"lo\": 2500, \"hi\": 3000},\n- \"tungsten\": {\"lo\": 3000, \"hi\": 3500},\n- \"fluorescent\": {\"lo\": 4000, \"hi\": 4700},\n- \"indoor\": {\"lo\": 3000, \"hi\": 5000},\n- \"daylight\": {\"lo\": 5500, \"hi\": 6500},\n- \"cloudy\": {\"lo\": 7000, \"hi\": 8600}\n- },\n- \"bayes\": 1\n- },\n- \"rpi.agc\": {\n- \"metering_modes\": {\n- \"centre-weighted\": {\n- \"weights\": [3, 3, 3, 2, 2, 2, 2, 1, 1, 1, 1, 0, 0, 0, 0]\n- },\n- \"spot\": {\n- \"weights\": [2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n- },\n- \"matrix\": {\n- \"weights\": [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]\n- }\n- },\n- \"exposure_modes\": {\n- \"normal\": {\n- \"shutter\": [100, 10000, 30000, 60000, 120000],\n- \"gain\": [1.0, 2.0, 4.0, 6.0, 6.0]\n- },\n- \"short\": {\n- \"shutter\": [100, 5000, 10000, 20000, 120000],\n- \"gain\": [1.0, 2.0, 4.0, 6.0, 6.0]\n- }\n- },\n- \"constraint_modes\": {\n- \"normal\": [\n- {\"bound\": \"LOWER\", \"q_lo\": 0.98, \"q_hi\": 1.0, \"y_target\": [0, 0.5, 1000, 0.5]}\n- ],\n- \"highlight\": [\n- {\"bound\": \"LOWER\", \"q_lo\": 0.98, \"q_hi\": 1.0, \"y_target\": [0, 0.5, 1000, 0.5]},\n- {\"bound\": \"UPPER\", \"q_lo\": 0.98, \"q_hi\": 1.0, \"y_target\": [0, 0.8, 1000, 0.8]}\n- ]\n- },\n- \"y_target\": [0, 0.16, 1000, 0.165, 10000, 0.17]\n- },\n- \"rpi.alsc\": {\n- 'omega': 1.3,\n- 'n_iter': 100,\n- 'luminance_strength': 0.7,\n- },\n- \"rpi.contrast\": {\n- \"ce_enable\": 1,\n- \"gamma_curve\": [\n- 0, 0,\n- 1024, 5040,\n- 2048, 9338,\n- 3072, 12356,\n- 4096, 15312,\n- 5120, 18051,\n- 6144, 20790,\n- 7168, 23193,\n- 8192, 25744,\n- 9216, 27942,\n- 10240, 30035,\n- 11264, 32005,\n- 12288, 33975,\n- 13312, 35815,\n- 14336, 37600,\n- 15360, 39168,\n- 16384, 40642,\n- 18432, 43379,\n- 20480, 45749,\n- 22528, 47753,\n- 24576, 49621,\n- 26624, 51253,\n- 28672, 52698,\n- 30720, 53796,\n- 32768, 54876,\n- 36864, 57012,\n- 40960, 58656,\n- 45056, 59954,\n- 49152, 61183,\n- 53248, 62355,\n- 57344, 63419,\n- 61440, 64476,\n- 65535, 65535\n- ]\n- },\n- \"rpi.ccm\": {\n- },\n- \"rpi.sharpen\": {\n- }\n- }\n+\n+ self.json = json\n+\n \n \"\"\"\n Perform colour correction calibrations by comparing macbeth patch colours\n to standard macbeth chart colours.\n \"\"\"\n- def ccm_cal(self, do_alsc_colour):\n+ def ccm_cal(self, do_alsc_colour, grid_size):\n if 'rpi.ccm' in self.disable:\n return 1\n print('\\nStarting CCM calibration')\n@@ -245,7 +133,7 @@ class Camera:\n Do CCM calibration\n \"\"\"\n try:\n- ccms = ccm(self, cal_cr_list, cal_cb_list)\n+ ccms = ccm(self, cal_cr_list, cal_cb_list, grid_size)\n except ArithmeticError:\n print('ERROR: Matrix is singular!\\nTake new pictures and try again...')\n self.log += '\\nERROR: Singular matrix encountered during fit!'\n@@ -263,7 +151,7 @@ class Camera:\n various colour temperatures, as well as providing a maximum 'wiggle room'\n distance from this curve (transverse_neg/pos).\n \"\"\"\n- def awb_cal(self, greyworld, do_alsc_colour):\n+ def awb_cal(self, greyworld, do_alsc_colour, grid_size):\n if 'rpi.awb' in self.disable:\n return 1\n print('\\nStarting AWB calibration')\n@@ -306,7 +194,7 @@ class Camera:\n call calibration function\n \"\"\"\n plot = \"rpi.awb\" in self.plot\n- awb_out = awb(self, cal_cr_list, cal_cb_list, plot)\n+ awb_out = awb(self, cal_cr_list, cal_cb_list, plot, grid_size)\n ct_curve, transverse_neg, transverse_pos = awb_out\n \"\"\"\n write output to json\n@@ -324,7 +212,7 @@ class Camera:\n colour channel seperately, and then partially corrects for vignetting.\n The extent of the correction depends on the 'luminance_strength' parameter.\n \"\"\"\n- def alsc_cal(self, luminance_strength, do_alsc_colour):\n+ def alsc_cal(self, luminance_strength, do_alsc_colour, grid_size):\n if 'rpi.alsc' in self.disable:\n return 1\n print('\\nStarting ALSC calibration')\n@@ -347,7 +235,7 @@ class Camera:\n call calibration function\n \"\"\"\n plot = \"rpi.alsc\" in self.plot\n- alsc_out = alsc_all(self, do_alsc_colour, plot)\n+ alsc_out = alsc_all(self, do_alsc_colour, plot, grid_size)\n cal_cr_list, cal_cb_list, luminance_lut, av_corn = alsc_out\n \"\"\"\n write output to json and finish if not do_alsc_colour\n@@ -393,7 +281,7 @@ class Camera:\n \"\"\"\n obtain worst-case scenario residual sigmas\n \"\"\"\n- sigma_r, sigma_b = get_sigma(self, cal_cr_list, cal_cb_list)\n+ sigma_r, sigma_b = get_sigma(self, cal_cr_list, cal_cb_list, grid_size)\n \"\"\"\n write output to json\n \"\"\"\n@@ -509,19 +397,20 @@ class Camera:\n \"\"\"\n writes the json dictionary to the raw json file then make pretty\n \"\"\"\n- def write_json(self):\n+ def write_json(self, version=2.0, target='bcm2835', grid_size=(16, 12)):\n \"\"\"\n Write json dictionary to file using our version 2 format\n \"\"\"\n \n out_json = {\n- \"version\": 2.0,\n- 'target': 'bcm2835',\n+ \"version\": version,\n+ 'target': target if target != 'vc4' else 'bcm2835',\n \"algorithms\": [{name: data} for name, data in self.json.items()],\n }\n \n with open(self.jf, 'w') as f:\n- f.write(pretty_print(out_json))\n+ f.write(pretty_print(out_json,\n+ custom_elems={'table': grid_size[0], 'luminance_lut': grid_size[0]}))\n \n \"\"\"\n add a new section to the log file\n@@ -712,7 +601,7 @@ class Camera:\n return 0\n \n \n-def run_ctt(json_output, directory, config, log_output, alsc_only=False):\n+def run_ctt(json_output, directory, config, log_output, json_template, grid_size, target, alsc_only=False):\n \"\"\"\n check input files are jsons\n \"\"\"\n@@ -748,7 +637,7 @@ def run_ctt(json_output, directory, config, log_output, alsc_only=False):\n greyworld = get_config(awb_d, \"greyworld\", 0, 'bool')\n alsc_d = get_config(configs, \"alsc\", {}, 'dict')\n do_alsc_colour = get_config(alsc_d, \"do_alsc_colour\", 1, 'bool')\n- luminance_strength = get_config(alsc_d, \"luminance_strength\", 0.5, 'num')\n+ luminance_strength = get_config(alsc_d, \"luminance_strength\", 0.8, 'num')\n blacklevel = get_config(configs, \"blacklevel\", -1, 'num')\n macbeth_d = get_config(configs, \"macbeth\", {}, 'dict')\n mac_small = get_config(macbeth_d, \"small\", 0, 'bool')\n@@ -772,7 +661,7 @@ def run_ctt(json_output, directory, config, log_output, alsc_only=False):\n initialise tuning tool and load images\n \"\"\"\n try:\n- Cam = Camera(json_output)\n+ Cam = Camera(json_output, json=json_template)\n Cam.log_user_input(json_output, directory, config, log_output)\n if alsc_only:\n disable = set(Cam.json.keys()).symmetric_difference({\"rpi.alsc\"})\n@@ -794,14 +683,16 @@ def run_ctt(json_output, directory, config, log_output, alsc_only=False):\n Cam.json['rpi.black_level']['black_level'] = Cam.blacklevel_16\n Cam.json_remove(disable)\n print('\\nSTARTING CALIBRATIONS')\n- Cam.alsc_cal(luminance_strength, do_alsc_colour)\n+ Cam.alsc_cal(luminance_strength, do_alsc_colour, grid_size)\n Cam.geq_cal()\n Cam.lux_cal()\n Cam.noise_cal()\n- Cam.awb_cal(greyworld, do_alsc_colour)\n- Cam.ccm_cal(do_alsc_colour)\n+ Cam.cac_cal(do_alsc_colour)\n+ Cam.awb_cal(greyworld, do_alsc_colour, grid_size)\n+ Cam.ccm_cal(do_alsc_colour, grid_size)\n+\n print('\\nFINISHED CALIBRATIONS')\n- Cam.write_json()\n+ Cam.write_json(target=target, grid_size=grid_size)\n Cam.write_log(log_output)\n print('\\nCalibrations written to: '+json_output)\n if log_output is None:\n@@ -810,28 +701,3 @@ def run_ctt(json_output, directory, config, log_output, alsc_only=False):\n pass\n else:\n Cam.write_log(log_output)\n-\n-\n-if __name__ == '__main__':\n- \"\"\"\n- initialise calibration\n- \"\"\"\n- if len(sys.argv) == 1:\n- print(\"\"\"\n- Pisp Camera Tuning Tool version 1.0\n-\n- Required Arguments:\n- '-i' : Calibration image directory.\n- '-o' : Name of output json file.\n-\n- Optional Arguments:\n- '-c' : Config file for the CTT. If not passed, default parameters used.\n- '-l' : Name of output log file. If not passed, 'ctt_log.txt' used.\n- \"\"\")\n- quit(0)\n- else:\n- \"\"\"\n- parse input arguments\n- \"\"\"\n- json_output, directory, config, log_output = parse_input()\n- run_ctt(json_output, directory, config, log_output)\ndiff --git a/utils/raspberrypi/ctt/ctt_vc4.py b/utils/raspberrypi/ctt/ctt_vc4.py\nnew file mode 100755\nindex 00000000..86acfd47\n--- /dev/null\n+++ b/utils/raspberrypi/ctt/ctt_vc4.py\n@@ -0,0 +1,157 @@\n+#!/usr/bin/env python3\n+#\n+# SPDX-License-Identifier: BSD-2-Clause\n+#\n+# Copyright (C) 2019, Raspberry Pi Ltd\n+#\n+# ctt_vc4.py - camera tuning tool for VC4 platforms\n+\n+import os\n+import sys\n+\n+from ctt_run import run_ctt\n+from ctt_tools import parse_input\n+\n+json_template = {\n+ \"rpi.black_level\": {\n+ \"black_level\": 4096\n+ },\n+ \"rpi.dpc\": {\n+ },\n+ \"rpi.lux\": {\n+ \"reference_shutter_speed\": 10000,\n+ \"reference_gain\": 1,\n+ \"reference_aperture\": 1.0\n+ },\n+ \"rpi.noise\": {\n+ },\n+ \"rpi.geq\": {\n+ },\n+ \"rpi.sdn\": {\n+ },\n+ \"rpi.awb\": {\n+ \"priors\": [\n+ {\"lux\": 0, \"prior\": [2000, 1.0, 3000, 0.0, 13000, 0.0]},\n+ {\"lux\": 800, \"prior\": [2000, 0.0, 6000, 2.0, 13000, 2.0]},\n+ {\"lux\": 1500, \"prior\": [2000, 0.0, 4000, 1.0, 6000, 6.0, 6500, 7.0, 7000, 1.0, 13000, 1.0]}\n+ ],\n+ \"modes\": {\n+ \"auto\": {\"lo\": 2500, \"hi\": 8000},\n+ \"incandescent\": {\"lo\": 2500, \"hi\": 3000},\n+ \"tungsten\": {\"lo\": 3000, \"hi\": 3500},\n+ \"fluorescent\": {\"lo\": 4000, \"hi\": 4700},\n+ \"indoor\": {\"lo\": 3000, \"hi\": 5000},\n+ \"daylight\": {\"lo\": 5500, \"hi\": 6500},\n+ \"cloudy\": {\"lo\": 7000, \"hi\": 8600}\n+ },\n+ \"bayes\": 1\n+ },\n+ \"rpi.agc\": {\n+ \"metering_modes\": {\n+ \"centre-weighted\": {\n+ \"weights\": [3, 3, 3, 2, 2, 2, 2, 1, 1, 1, 1, 0, 0, 0, 0]\n+ },\n+ \"spot\": {\n+ \"weights\": [2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n+ },\n+ \"matrix\": {\n+ \"weights\": [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]\n+ }\n+ },\n+ \"exposure_modes\": {\n+ \"normal\": {\n+ \"shutter\": [100, 10000, 30000, 60000, 120000],\n+ \"gain\": [1.0, 2.0, 4.0, 6.0, 6.0]\n+ },\n+ \"short\": {\n+ \"shutter\": [100, 5000, 10000, 20000, 120000],\n+ \"gain\": [1.0, 2.0, 4.0, 6.0, 6.0]\n+ }\n+ },\n+ \"constraint_modes\": {\n+ \"normal\": [\n+ {\"bound\": \"LOWER\", \"q_lo\": 0.98, \"q_hi\": 1.0, \"y_target\": [0, 0.5, 1000, 0.5]}\n+ ],\n+ \"highlight\": [\n+ {\"bound\": \"LOWER\", \"q_lo\": 0.98, \"q_hi\": 1.0, \"y_target\": [0, 0.5, 1000, 0.5]},\n+ {\"bound\": \"UPPER\", \"q_lo\": 0.98, \"q_hi\": 1.0, \"y_target\": [0, 0.8, 1000, 0.8]}\n+ ]\n+ },\n+ \"y_target\": [0, 0.16, 1000, 0.165, 10000, 0.17]\n+ },\n+ \"rpi.alsc\": {\n+ 'omega': 1.3,\n+ 'n_iter': 100,\n+ 'luminance_strength': 0.7,\n+ },\n+ \"rpi.contrast\": {\n+ \"ce_enable\": 1,\n+ \"gamma_curve\": [\n+ 0, 0,\n+ 1024, 5040,\n+ 2048, 9338,\n+ 3072, 12356,\n+ 4096, 15312,\n+ 5120, 18051,\n+ 6144, 20790,\n+ 7168, 23193,\n+ 8192, 25744,\n+ 9216, 27942,\n+ 10240, 30035,\n+ 11264, 32005,\n+ 12288, 33975,\n+ 13312, 35815,\n+ 14336, 37600,\n+ 15360, 39168,\n+ 16384, 40642,\n+ 18432, 43379,\n+ 20480, 45749,\n+ 22528, 47753,\n+ 24576, 49621,\n+ 26624, 51253,\n+ 28672, 52698,\n+ 30720, 53796,\n+ 32768, 54876,\n+ 36864, 57012,\n+ 40960, 58656,\n+ 45056, 59954,\n+ 49152, 61183,\n+ 53248, 62355,\n+ 57344, 63419,\n+ 61440, 64476,\n+ 65535, 65535\n+ ]\n+ },\n+ \"rpi.ccm\": {\n+ },\n+ \"rpi.sharpen\": {\n+ }\n+}\n+\n+grid_size = (16, 12)\n+\n+target = 'bcm2835'\n+\n+if __name__ == '__main__':\n+ \"\"\"\n+ initialise calibration\n+ \"\"\"\n+ if len(sys.argv) == 1:\n+ print(\"\"\"\n+ VC4 Camera Tuning Tool version 1.0\n+\n+ Required Arguments:\n+ '-i' : Calibration image directory.\n+ '-o' : Name of output json file.\n+\n+ Optional Arguments:\n+ '-c' : Config file for the CTT. If not passed, default parameters used.\n+ '-l' : Name of output log file. If not passed, 'ctt_log.txt' used.\n+ \"\"\")\n+ quit(0)\n+ else:\n+ \"\"\"\n+ parse input arguments\n+ \"\"\"\n+ json_output, directory, config, log_output = parse_input()\n+ run_ctt(json_output, directory, config, log_output, json_template, grid_size, target)\n","prefixes":["1/6"]}