{"id":18818,"url":"https://patchwork.libcamera.org/api/1.1/patches/18818/?format=json","web_url":"https://patchwork.libcamera.org/patch/18818/","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":"<20230707031702.603261-4-ben.benson@raspberrypi.com>","date":"2023-07-07T03:17:02","name":"[libcamera-devel,v2,3/3] utils: raspberrypi: ctt: Code tidying","commit_ref":"09dd65442b62f4069189f7a92f2b224687257e52","pull_url":null,"state":"accepted","archived":false,"hash":"11d082c82a371c8f7b7e7dabac0e13ca418796b8","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/18818/mbox/","series":[{"id":3969,"url":"https://patchwork.libcamera.org/api/1.1/series/3969/?format=json","web_url":"https://patchwork.libcamera.org/project/libcamera/list/?series=3969","date":"2023-07-07T03:16:59","name":"Raspberry Pi Color Matrix and Tuning Tool Improvements","version":2,"mbox":"https://patchwork.libcamera.org/series/3969/mbox/"}],"comments":"https://patchwork.libcamera.org/api/patches/18818/comments/","check":"pending","checks":"https://patchwork.libcamera.org/api/patches/18818/checks/","tags":{},"headers":{"Return-Path":"<libcamera-devel-bounces@lists.libcamera.org>","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 0F7CBC3243\n\tfor <parsemail@patchwork.libcamera.org>;\n\tThu, 13 Jul 2023 10:35:25 +0000 (UTC)","from lancelot.ideasonboard.com (localhost [IPv6:::1])\n\tby lancelot.ideasonboard.com (Postfix) with ESMTP id A5098628BE;\n\tThu, 13 Jul 2023 12:35:24 +0200 (CEST)","from mail-wm1-x332.google.com (mail-wm1-x332.google.com\n\t[IPv6:2a00:1450:4864:20::332])\n\tby lancelot.ideasonboard.com (Postfix) with ESMTPS id 00EBB628BC\n\tfor <libcamera-devel@lists.libcamera.org>;\n\tThu, 13 Jul 2023 12:35:20 +0200 (CEST)","by mail-wm1-x332.google.com with SMTP id\n\t5b1f17b1804b1-3fbc59de009so4449075e9.3\n\tfor <libcamera-devel@lists.libcamera.org>;\n\tThu, 13 Jul 2023 03:35:19 -0700 (PDT)","from localhost.localdomain ([93.93.133.154])\n\tby smtp.gmail.com with ESMTPSA id\n\tr8-20020a056000014800b0030fa3567541sm7551143wrx.48.2023.07.13.03.35.18\n\t(version=TLS1_3 cipher=TLS_AES_256_GCM_SHA384 bits=256/256);\n\tThu, 13 Jul 2023 03:35:19 -0700 (PDT)"],"DKIM-Signature":["v=1; 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\n\tThu, 13 Jul 2023 03:35:19 -0700 (PDT)","To":"libcamera-devel@lists.libcamera.org","Date":"Fri,  7 Jul 2023 04:17:02 +0100","Message-Id":"<20230707031702.603261-4-ben.benson@raspberrypi.com>","X-Mailer":"git-send-email 2.34.1","In-Reply-To":"<20230707031702.603261-1-ben.benson@raspberrypi.com>","References":"<20230707031702.603261-1-ben.benson@raspberrypi.com>","MIME-Version":"1.0","Content-Transfer-Encoding":"8bit","Subject":"[libcamera-devel] [PATCH v2 3/3] utils: raspberrypi: ctt: Code\n\ttidying","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>","List-Archive":"<https://lists.libcamera.org/pipermail/libcamera-devel/>","List-Post":"<mailto:libcamera-devel@lists.libcamera.org>","List-Help":"<mailto:libcamera-devel-request@lists.libcamera.org?subject=help>","List-Subscribe":"<https://lists.libcamera.org/listinfo/libcamera-devel>,\n\t<mailto:libcamera-devel-request@lists.libcamera.org?subject=subscribe>","From":"Ben Benson via libcamera-devel <libcamera-devel@lists.libcamera.org>","Reply-To":"Ben Benson <ben.benson@raspberrypi.com>","Cc":"Ben Benson <ben.benson@raspberrypi.com>","Errors-To":"libcamera-devel-bounces@lists.libcamera.org","Sender":"\"libcamera-devel\" <libcamera-devel-bounces@lists.libcamera.org>"},"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 <ben.benson@raspberrypi.com>\n---\n utils/raspberrypi/ctt/ctt_ccm.py | 61 ++++++++++++++------------------\n 1 file changed, 27 insertions(+), 34 deletions(-)","diff":"diff --git a/utils/raspberrypi/ctt/ctt_ccm.py b/utils/raspberrypi/ctt/ctt_ccm.py\nindex 49159535..a09bfd09 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+    # Produce array of LAB values for ideal color chart\n+    m_lab = [colors.RGB_to_LAB(color / 256) for color in m_srgb]\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@@ -188,7 +183,7 @@ def ccm(Cam, cal_cr_list, cal_cb_list):\n         We use our old CCM as the initial guess for the program to find the\n         optimised matrix\n         '''\n-        result = minimize(guess, x0, args=(r, g, b, m_lab), tol=0.0000000001)\n+        result = minimize(guess, x0, args=(r, g, b, m_lab), tol=0.01)\n         '''\n         This produces a color matrix which has the lowest delta E possible,\n         based off the input data. Note it is impossible for this to reach\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 +209,21 @@ 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+        formatted_optimised_ccm = np.array(optimised_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-            optimised_ccm_applied_rgb = np.dot(formatted_optimised_ccm, RGB / 256)\n+\n+        for RGB in zip(r, g, b):\n+            ccm_applied_rgb = np.dot(formatted_ccm, (np.array(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, np.array(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-        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 matrices\n         '''\n@@ -303,9 +298,8 @@ 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-        rgb_post_ccm = np.dot(ccm, RGB)  # This is RGB values after the color correction matrix has been applied\n+    for RGB in zip(r, g, b):\n+        rgb_post_ccm = np.dot(ccm, np.array(RGB) / 256)  # 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     return (sumde(realrgb, m_lab) / 24)  # returns an average result of delta E\n@@ -315,12 +309,12 @@ 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 +324,8 @@ 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","prefixes":["libcamera-devel","v2","3/3"]}