from cffi import FFI
from PIL import Image
import numpy as np
import cv2, time

ffi = FFI()
ffi.cdef("""
    int test(int);

    typedef void* haarclassifier;
    haarclassifier classifier_new(char *filename);
    void scan_image(haarclassifier, size_t width,size_t height, char *input, char *buffer, size_t length, bool debug);
""")

# C = ffi.dlopen("/home/ruben/Documents/Projecten/2020/rust/testproject/target/debug/libvisual_haarcascades_lib.so")
C = ffi.dlopen("visualhaar/target/debug/libvisual_haarcascades_lib.so")

print(C.test(9))
# i = Image.open("/home/ruben/Documents/Projecten/2020/rust/lena_orig.png")
# a= np.array(i)
a= cv2.imread("/home/ruben/Documents/Projecten/2020/rust/lena_orig.png")

capture = cv2.VideoCapture(2)

print("Buffer", capture.get(cv2.CAP_PROP_BUFFERSIZE))
capture.set(cv2.CAP_PROP_BUFFERSIZE, 1)

while True:
    ret, a = capture.read()
    print(a.shape)

    # i = Image.open("Marjo.jpg")
    width = int(a.shape[1]/4)
    height = int(a.shape[0]/4)

    image = cv2.resize(a, (width,height))

    pixel_format = "RGB" #The raytracer only supports one format
    bytes_per_pixel = 3
    buffer_len = width * height * bytes_per_pixel
    buffer = ffi.new("char[]", buffer_len)
    # buffer2 = ffi.from_buffer("char[]", (i.tobytes("raw","RGB")))
    buffer2 = ffi.from_buffer("char[]", image.tobytes())


    filename = "/home/ruben/Documents/Projecten/2020/rust/testproject/haarcascade_frontalface_alt2.xml".encode('ascii')
    fn = ffi.new("char[]", filename)
    # fn = ffi.string(filename)

    print("Initialise...")
    haar = C.classifier_new(fn)
    # i = Image.open("/home/ruben/Documents/Projecten/2020/rust/lena_orig.png")
    # data = i.tobytes("raw", "RGB")

    print('scan!')
    start=time.time()
    C.scan_image(haar, width, height, buffer2, buffer, buffer_len, True)


    print(f"scanned in {time.time() - start}s", buffer)

    # img = Image.frombuffer(pixel_format, (width, height), ffi.buffer(buffer),
    #             "raw", pixel_format, 0, 1)
    # img = Image.frombuffer(pixel_format, (width, height), ffi.buffer(buffer),
    #             "raw", pixel_format, 0, 1)
    img = Image.frombuffer(pixel_format, (width, height), ffi.buffer(buffer),
                "raw", pixel_format, 0, 1)
    a= np.array(img)
    # a= np.frombuffer(ffi.buffer(buffer))
    # a.reshape((height, width, bytes_per_pixel))
    a = a[:, :, ::-1]
    img_concate_Verti1 = np.concatenate((image,a),axis=0)
    cv2.imshow("image",img_concate_Verti1)

    # Hit 'q' on the keyboard to quit!
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

    # img.show()
    # class Scene(object):
    #     def __init__(self, width, height, fov, shadow_bias, max_recursion_depth):
    #         self.__width = width
    #         self.__height = height
    #         self.__obj = C.scene_new(width, height, fov, shadow_bias, max_recursion_depth)

    #     def render(self):
    #         pixel_format = "RGBA" #The raytracer only supports one format
    #         bytes_per_pixel = 4

    #         buffer_len = self.__width * self.__height * bytes_per_pixel
    #         buffer = ffi.new("char[]", buffer_len)
    #         C.scene_render(self.__obj, buffer, buffer_len)
    #         return Image.frombuffer(pixel_format, (self.__width, self.__height), ffi.buffer(buffer),
    #             "raw", pixel_format, 0, 1)

capture.release()