{"id":18802,"url":"https://patchwork.libcamera.org/api/1.1/patches/18802/?format=json","web_url":"https://patchwork.libcamera.org/patch/18802/","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":"<20230706013926.218131-4-ben.benson@raspberrypi.com>","date":"2023-07-06T01:39:26","name":"[libcamera-devel,3/3] utils: raspberrypi: ctt: Code tidying","commit_ref":null,"pull_url":null,"state":"accepted","archived":false,"hash":"35d9dd716c4d1ccc4f6e994f5600a681be382d9f","submitter":{"id":171,"url":"https://patchwork.libcamera.org/api/1.1/people/171/?format=json","name":"Ben Benson","email":"ben.benson@raspberrypi.com"},"delegate":null,"mbox":"https://patchwork.libcamera.org/patch/18802/mbox/","series":[{"id":3963,"url":"https://patchwork.libcamera.org/api/1.1/series/3963/?format=json","web_url":"https://patchwork.libcamera.org/project/libcamera/list/?series=3963","date":"2023-07-06T01:39:23","name":"Raspberry Pi Color Matrix and Tuning Tool Improvements","version":1,"mbox":"https://patchwork.libcamera.org/series/3963/mbox/"}],"comments":"https://patchwork.libcamera.org/api/patches/18802/comments/","check":"pending","checks":"https://patchwork.libcamera.org/api/patches/18802/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 C4146C32AA\n\tfor ;\n\tFri, 7 Jul 2023 13:41:26 +0000 (UTC)","from lancelot.ideasonboard.com 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x=1691323666;\n\th=content-transfer-encoding:mime-version:references:in-reply-to\n\t:message-id:date:subject:cc:to:from:x-gm-message-state:from:to:cc\n\t:subject:date:message-id:reply-to;\n\tbh=DYyHsn0OMeUjMVdng7IjTkP1xYPflT8FFtPeTKBCgwk=;\n\tb=LWbzitKzNETMbLxifxoJeAD/ieu8dip2lJUfbwOV3t5EZjEe1/1fIL09eqkSlpxCwS\n\tvbQgoxZtUp99sJX0s/ohonNV+eO1KKjTbBeOccL4Iq/TgMCVxwohrpUisF2v5+daZhIr\n\tRMUipVqg31KC5bOt65hfiLypB8YzHH3tc54eKMNqoU6RpbNJJ0vXpJhsLpKGXotM1We8\n\tDD4CO0NXqmr9Q6eDQaUpzkuLhMqdqOrjC7TMlw9ISW5s+DKs+pWAMEWPoUKmnKxWeVSG\n\tdDBo9hNQupyPYHW/TuERldgPCpMv1dtXnessDeyuDwfm18Qsa32y/yAkN6Aql5e47E1A\n\tl1cQ==","X-Gm-Message-State":"ABy/qLYordUo9/8kj17pVM5GSiFpzT+63nE/uwf1v8BI5WC8h7wGZH3Y\n\teYwZNoS08rHpQnANZRpCFzJdW+yWlqo7coWgjSRvhg==","X-Google-Smtp-Source":"APBJJlEB6+VmnvLmF/D4mhaS3u6j7o0BBMtD/S51UWLRWjrAeQHXzaN0jX/7PSGaEC/mcAhQe5n/ng==","X-Received":"by 2002:a05:6512:b8b:b0:4fb:8ff3:1f72 with SMTP id\n\tb11-20020a0565120b8b00b004fb8ff31f72mr5109669lfv.1.1688731665815; \n\tFri, 07 Jul 2023 05:07:45 -0700 (PDT)","To":"libcamera-devel@lists.libcamera.org","Date":"Thu, 6 Jul 2023 02:39:26 +0100","Message-Id":"<20230706013926.218131-4-ben.benson@raspberrypi.com>","X-Mailer":"git-send-email 2.34.1","In-Reply-To":"<20230706013926.218131-1-ben.benson@raspberrypi.com>","References":"<20230706013926.218131-1-ben.benson@raspberrypi.com>","MIME-Version":"1.0","Content-Transfer-Encoding":"8bit","X-Mailman-Approved-At":"Fri, 07 Jul 2023 15:41:21 +0200","Subject":"[libcamera-devel] [PATCH 3/3] utils: raspberrypi: ctt: Code tidying","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","From":"Ben Benson via libcamera-devel ","Reply-To":"Ben Benson ","Cc":"Ben Benson ","Errors-To":"libcamera-devel-bounces@lists.libcamera.org","Sender":"\"libcamera-devel\" "},"content":"Altered the way that some lines are laid out, made functions\nmore attractive to look at, and tidied up messy areas.\n\nSigned-off-by Ben Benson \n---\n utils/raspberrypi/ctt/ctt_ccm.py | 61 +++++++++++++++-----------------\n 1 file changed, 29 insertions(+), 32 deletions(-)","diff":"diff --git a/utils/raspberrypi/ctt/ctt_ccm.py b/utils/raspberrypi/ctt/ctt_ccm.py\nindex bd44b4d8..85ca6827 100644\n--- a/utils/raspberrypi/ctt/ctt_ccm.py\n+++ b/utils/raspberrypi/ctt/ctt_ccm.py\n@@ -47,11 +47,8 @@ def degamma(x):\n \n \n def gamma(x):\n- # return (x * * (1 / 2.4) * 1.055 - 0.055)\n- e = []\n- for i in range(len(x)):\n- e.append(((x[i] / 255) ** (1 / 2.4) * 1.055 - 0.055) * 255)\n- return e\n+ # Take 3 long array of color values and gamma them\n+ return [((colour / 255) ** (1 / 2.4) * 1.055 - 0.055) * 255 for colour in x]\n \n \n \"\"\"\n@@ -96,10 +93,8 @@ def ccm(Cam, cal_cr_list, cal_cb_list):\n \"\"\"\n m_srgb = degamma(m_rgb) # now in 16 bit color.\n \n- m_lab = []\n- for col in m_srgb:\n- m_lab.append(colors.RGB_to_LAB(col / 256))\n- # This produces matrix of LAB values for ideal color chart)\n+ m_lab = [colors.RGB_to_LAB(color / 256) for color in m_srgb]\n+ # This produces array of LAB values for ideal color chart)\n \n \"\"\"\n reorder reference values to match how patches are ordered\n@@ -168,7 +163,7 @@ def ccm(Cam, cal_cr_list, cal_cb_list):\n sumde = 0\n ccm = do_ccm(r, g, b, m_srgb)\n # This is the initial guess that our optimisation code works with.\n-\n+ original_ccm = ccm\n r1 = ccm[0]\n r2 = ccm[1]\n g1 = ccm[3]\n@@ -199,12 +194,13 @@ def ccm(Cam, cal_cr_list, cal_cb_list):\n [r1, r2, g1, g2, b1, b2] = result.x\n # The new, optimised color correction matrix values\n optimised_ccm = [r1, r2, (1 - r1 - r2), g1, g2, (1 - g1 - g2), b1, b2, (1 - b1 - b2)]\n+\n # This is the optimised Color Matrix (preserving greys by summing rows up to 1)\n Cam.log += str(optimised_ccm)\n Cam.log += \"\\n Old Color Correction Matrix Below \\n\"\n Cam.log += str(ccm)\n \n- formatted_ccm = np.array(ccm).reshape((3, 3))\n+ formatted_ccm = np.array(original_ccm).reshape((3, 3))\n \n '''\n below is a whole load of code that then applies the latest color\n@@ -213,22 +209,23 @@ def ccm(Cam, cal_cr_list, cal_cb_list):\n '''\n optimised_ccm_rgb = [] # Original Color Corrected Matrix RGB / LAB\n optimised_ccm_lab = []\n- for w in range(24):\n- RGB = np.array([r[w], g[w], b[w]])\n- ccm_applied_rgb = np.dot(formatted_ccm, (RGB / 256))\n- optimised_ccm_rgb.append(gamma(ccm_applied_rgb))\n- optimised_ccm_lab.append(colors.RGB_to_LAB(ccm_applied_rgb))\n \n formatted_optimised_ccm = np.array(ccm).reshape((3, 3))\n after_gamma_rgb = []\n after_gamma_lab = []\n- for w in range(24):\n- RGB = np.array([r[w], g[w], b[w]])\n+\n+ for red, green, blue in zip(r, g, b):\n+ RGB = np.array([red, green, blue])\n+ ccm_applied_rgb = np.dot(formatted_ccm, (RGB / 256))\n+ optimised_ccm_rgb.append(gamma(ccm_applied_rgb))\n+ optimised_ccm_lab.append(colors.RGB_to_LAB(ccm_applied_rgb))\n+\n optimised_ccm_applied_rgb = np.dot(formatted_optimised_ccm, RGB / 256)\n after_gamma_rgb.append(gamma(optimised_ccm_applied_rgb))\n after_gamma_lab.append(colors.RGB_to_LAB(optimised_ccm_applied_rgb))\n+\n '''\n- Gamma After RGB / LAB\n+ Gamma After RGB / LAB - not used in calculations, only used for visualisation\n We now want to spit out some data that shows\n how the optimisation has improved the color matricies\n '''\n@@ -303,8 +300,8 @@ def guess(x0, r, g, b, m_lab): # provides a method of numerical feedback f\n def transform_and_evaluate(ccm, r, g, b, m_lab): # Transforms colors to LAB and applies the correction matrix\n # create list of matrix changed colors\n realrgb = []\n- for i in range(len(r)):\n- RGB = np.array([r[i], g[i], b[i]])\n+ for red, green, blue in zip(r, g, b):\n+ RGB = np.array([red, green, blue])\n rgb_post_ccm = np.dot(ccm, RGB) # This is RGB values after the color correction matrix has been applied\n realrgb.append(colors.RGB_to_LAB(rgb_post_ccm))\n # now compare that with m_lab and return numeric result, averaged for each patch\n@@ -315,12 +312,12 @@ def sumde(listA, listB):\n global typenum, test_patches\n sumde = 0\n maxde = 0\n- patchde = []\n- for i in range(len(listA)):\n- if maxde < (deltae(listA[i], listB[i])):\n- maxde = deltae(listA[i], listB[i])\n- patchde.append(deltae(listA[i], listB[i]))\n- sumde += deltae(listA[i], listB[i])\n+ patchde = [] # Create array of the delta E values for each patch. useful for optimisation of certain patches\n+ for listA_item, listB_item in zip(listA, listB):\n+ if maxde < (deltae(listA_item, listB_item)):\n+ maxde = deltae(listA_item, listB_item)\n+ patchde.append(deltae(listA_item, listB_item))\n+ sumde += deltae(listA_item, listB_item)\n '''\n The different options specified at the start allow for\n the maximum to be returned, average or specific patches\n@@ -330,9 +327,8 @@ def sumde(listA, listB):\n if typenum == 1:\n return maxde\n if typenum == 2:\n- output = 0\n- for y in range(len(test_patches)):\n- output += patchde[test_patches[y]] # grabs the specific patches (no need for averaging here)\n+ output = sum([patchde[test_patch] for test_patch in test_patches])\n+ # Selects only certain patches and returns the output for them\n return output\n \n \n@@ -341,8 +337,9 @@ calculates the ccm for an individual image.\n ccms are calculate in rgb space, and are fit by hand. Although it is a 3x3\n matrix, each row must add up to 1 in order to conserve greyness, simplifying\n calculation.\n-Should you want to fit them in another space (e.g. LAB) we wish you the best of\n-luck and send us the code when you are done! :-)\n+The initial CCM is calculated in RGB, and then optimised in LAB color space\n+This simplifies the initial calculation but then gets us the accuracy of\n+using LAB color space.\n \"\"\"\n \n \n","prefixes":["libcamera-devel","3/3"]}