96 lines
3.3 KiB
Python
96 lines
3.3 KiB
Python
from cffi import FFI
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from PIL import Image
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import numpy as np
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import cv2, time
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ffi = FFI()
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ffi.cdef("""
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int test(int);
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typedef void* haarclassifier;
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haarclassifier classifier_new(char *filename);
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void scan_image(haarclassifier, size_t width,size_t height, char *input, char *buffer, size_t length, bool debug);
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""")
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# C = ffi.dlopen("/home/ruben/Documents/Projecten/2020/rust/testproject/target/debug/libvisual_haarcascades_lib.so")
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C = ffi.dlopen("visualhaar/target/debug/libvisual_haarcascades_lib.so")
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print(C.test(9))
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# i = Image.open("/home/ruben/Documents/Projecten/2020/rust/lena_orig.png")
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# a= np.array(i)
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a= cv2.imread("/home/ruben/Documents/Projecten/2020/rust/lena_orig.png")
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capture = cv2.VideoCapture(2)
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print("Buffer", capture.get(cv2.CAP_PROP_BUFFERSIZE))
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capture.set(cv2.CAP_PROP_BUFFERSIZE, 1)
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while True:
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ret, a = capture.read()
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print(a.shape)
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# i = Image.open("Marjo.jpg")
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width = int(a.shape[1]/4)
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height = int(a.shape[0]/4)
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image = cv2.resize(a, (width,height))
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pixel_format = "RGB" #The raytracer only supports one format
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bytes_per_pixel = 3
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buffer_len = width * height * bytes_per_pixel
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buffer = ffi.new("char[]", buffer_len)
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# buffer2 = ffi.from_buffer("char[]", (i.tobytes("raw","RGB")))
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buffer2 = ffi.from_buffer("char[]", image.tobytes())
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filename = "/home/ruben/Documents/Projecten/2020/rust/testproject/haarcascade_frontalface_alt2.xml".encode('ascii')
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fn = ffi.new("char[]", filename)
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# fn = ffi.string(filename)
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print("Initialise...")
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haar = C.classifier_new(fn)
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# i = Image.open("/home/ruben/Documents/Projecten/2020/rust/lena_orig.png")
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# data = i.tobytes("raw", "RGB")
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print('scan!')
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start=time.time()
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C.scan_image(haar, width, height, buffer2, buffer, buffer_len, True)
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print(f"scanned in {time.time() - start}s", buffer)
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# img = Image.frombuffer(pixel_format, (width, height), ffi.buffer(buffer),
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# "raw", pixel_format, 0, 1)
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# img = Image.frombuffer(pixel_format, (width, height), ffi.buffer(buffer),
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# "raw", pixel_format, 0, 1)
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img = Image.frombuffer(pixel_format, (width, height), ffi.buffer(buffer),
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"raw", pixel_format, 0, 1)
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a= np.array(img)
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# a= np.frombuffer(ffi.buffer(buffer))
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# a.reshape((height, width, bytes_per_pixel))
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a = a[:, :, ::-1]
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img_concate_Verti1 = np.concatenate((image,a),axis=0)
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cv2.imshow("image",img_concate_Verti1)
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# Hit 'q' on the keyboard to quit!
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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# img.show()
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# class Scene(object):
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# def __init__(self, width, height, fov, shadow_bias, max_recursion_depth):
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# self.__width = width
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# self.__height = height
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# self.__obj = C.scene_new(width, height, fov, shadow_bias, max_recursion_depth)
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# def render(self):
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# pixel_format = "RGBA" #The raytracer only supports one format
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# bytes_per_pixel = 4
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# buffer_len = self.__width * self.__height * bytes_per_pixel
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# buffer = ffi.new("char[]", buffer_len)
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# C.scene_render(self.__obj, buffer, buffer_len)
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# return Image.frombuffer(pixel_format, (self.__width, self.__height), ffi.buffer(buffer),
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# "raw", pixel_format, 0, 1)
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capture.release() |