local opencv_lua = require("opencv_lua")
local cv = opencv_lua.cv

local img = cv.imread("lena.jpg")
cv.imshow("Image", img)
cv.waitKey()
cv.destroyAllWindows()

local opencv_lua = require("opencv_lua")
local cv = opencv_lua.cv
local int = opencv_lua.math.int

local camId = 0
local cap = cv.VideoCapture(camId)
if not cap:isOpened() then error("!>Error: cannot open the camera " .. camId) end

local CAP_FPS = 60
local CAP_SPF = int(1000 / CAP_FPS)

cap:set(cv.CAP_PROP_FRAME_WIDTH, 1280)
cap:set(cv.CAP_PROP_FRAME_HEIGHT, 720)
cap:set(cv.CAP_PROP_FPS, CAP_FPS)

while true do
    -- Without this, memory grows indefinitely
    collectgarbage()

    local start = cv.getTickCount()
    local read, frame = cap:read()
    if not read then
        io.stderr:write("!>Error: cannot read the camera.\n")
    end
    local fps = cv.getTickFrequency() / (cv.getTickCount() - start)

    -- Flip the image horizontally to give the mirror impression
    local frame = cv.flip(frame, 1)

    cv.putText(frame, string.format("FPS : %.2f", fps), { 10, 30 }, cv.FONT_HERSHEY_PLAIN, 2, {255, 0, 255}, 3)
    cv.imshow("capture camera", frame)

    local key = cv.waitKey(CAP_SPF)
    if key == 0x1b or key == string.byte("q") or key == string.byte("Q") then break end
end

cv.destroyAllWindows()

local opencv_lua = require("opencv_lua")
local cv = opencv_lua.cv

local img = cv.imread("lena.jpg")
local angle = 20
local scale = 1

local size = { img.width, img.height }
local center = { img.width / 2, img.height / 2 }
local M = cv.getRotationMatrix2D(center, -angle, scale)
local rotated = cv.warpAffine(img, M, size)

cv.imshow("Rotation", rotated)
cv.waitKey()
cv.destroyAllWindows()

local opencv_lua = require("opencv_lua")
local cv = opencv_lua.cv

local img = cv.imread("pic1.png")
local img_grey = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
local ret, thresh = cv.threshold(img_grey, 100, 255, cv.THRESH_BINARY)
local contours, hierarchy = cv.findContours(thresh, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)

print("Found " .. #contours .. " contours")

cv.drawContours(img, contours, -1, { 0, 0, 255 }, 2)

cv.imshow("Image", img)
cv.waitKey()
cv.destroyAllWindows()

local opencv_lua = require("opencv_lua")
local cv = opencv_lua.cv

--[[
Sources:
    https://docs.opencv.org/4.x/d4/dc6/tutorial_py_template_matching.html
--]]

local img_rgb = cv.imread("mario.png")
assert(not img_rgb:empty(), "file could not be read, check with os.path.exists()")
local img_gray = cv.cvtColor(img_rgb, cv.COLOR_BGR2GRAY)
local template = cv.imread("mario_coin.png", cv.IMREAD_GRAYSCALE)
assert(not template:empty(), "file could not be read, check with os.path.exists()")

local h, w = template.height, template.width

local res = cv.matchTemplate(img_gray, template, cv.TM_CCOEFF_NORMED)
local threshold = 0.8

-- transform into an lua table for faster processing in lua
local rows, cols = res.rows, res.cols
res = res:table()

for j = 1, rows do
    local y = j - 1
    for i = 1, cols do
        local x = i - 1
        if res[j][i] >= threshold then
            cv.rectangle(img_rgb, { x, y }, { x + w, y + h }, { 0, 0, 255 }, 2)
        end
    end
end

cv.imshow("res.png", img_rgb)
cv.waitKey()
cv.destroyAllWindows()

cv.normalize(src, dst, alpha, beta, norm_type, dtype, mask)
cv.normalize(src, dst, alpha, beta, norm_type, dtype, opencv_lua.kwargs({ mask = mask }))
cv.normalize(src, dst, alpha, beta, norm_type, opencv_lua.kwargs({ dtype = dtype, mask = mask }))
cv.normalize(src, dst, alpha, beta, opencv_lua.kwargs({ norm_type = norm_type, dtype = dtype, mask = mask }))
cv.normalize(src, dst, alpha, opencv_lua.kwargs({ beta = beta, norm_type = norm_type, dtype = dtype, mask = mask }))
cv.normalize(src, dst, opencv_lua.kwargs({ alpha = alpha, beta = beta, norm_type = norm_type, dtype = dtype, mask = mask }))
cv.normalize(src, opencv_lua.kwargs({ dst = dst, alpha = alpha, beta = beta, norm_type = norm_type, dtype = dtype, mask = mask }))
cv.normalize(opencv_lua.kwargs({ src = src, dst = dst, alpha = alpha, beta = beta, norm_type = norm_type, dtype = dtype, mask = mask }))

cv.normalize(src, dst, opencv_lua.kwargs({ norm_type = cv.NORM_L1 }))

local opencv_lua = require("opencv_lua")
local cv = opencv_lua.cv

local img = cv.imread(cv.samples.findFile("pic1.png"))
local img_grey = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
local ret, thresh = cv.threshold(img_grey, 100, 255, cv.THRESH_BINARY)
local contours, hierarchy = cv.findContours(thresh, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)

print("Found " .. #contours .. " contours")

cv.drawContours(img, contours, -1, { 0, 0, 255 }, 2)

cv.imshow("Image", img)
cv.waitKey()
cv.destroyAllWindows()

for i = 1, #contours do
    -- Notice the i - 1
    cv.drawContours(src, contours, i - 1, {0, 0, 255}, 2)
end

cv.ml.SVM.create(...)
cv.ml.SVM.C_SVC
cv.TermCriteria.MAX_ITER

local cap = cv.VideoCapture(0)
while true do
    -- Without this, memory grows indefinitely
    collectgarbage()

    local read, frame = cap:read()
    cv.imshow("capture camera", frame)
    if cv.waitKey(0) == 0x1b then break end
end

-- transform into an lua table for faster processing in lua
local rows, cols, type_ = res.rows, res.cols, res:type()
res = res:table()

for j = 1, rows do
    local y = j - 1
    for i = 1, cols do
        local x = i - 1
        if res[j][i] >= threshold then
            cv.rectangle(img_rgb, { x, y }, { x + w, y + h }, { 0, 0, 255 }, 2)
        end
    end
end

res = cv.Mat.createFromArray(res, type_)

local ffi = require("ffi")

local rows = 512
local cols = 512
local channels = 3
local mat = cv.Mat({ rows, cols, channels }, cv.CV_8U, 255.0)
local bytes = ffi.cast("unsigned char*", mat.data)

local sum = 0
for i = 0, rows - 1 do
    for j = 0, cols - 1 do
        for k = 0, channels - 1 do
            sum = sum + bytes[i * cols * channels + j * channels + k]
        end
    end
end