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modules/py_image: Replace unpack with ndarray creation.
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@ -6,6 +6,7 @@
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# This work is licensed under the MIT license, see the file LICENSE for details.
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import image
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from ulab import numpy as np
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class Normalization:
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@ -34,6 +35,7 @@ class Normalization:
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return n
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buffer, shape, dtype = args
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# Create an image using the input tensor as buffer.
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if len(shape) != 4:
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raise ValueError("Expected input tensor with shape: (1, H, W, C)")
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@ -42,12 +44,32 @@ class Normalization:
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raise ValueError("Expected batches to be 1")
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if c != 1 and c != 3:
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raise ValueError("Expected channels to be 1 or 3")
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# Place the image buffer at the end of the input buffer so we can convert it in-place.
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pixfmt = image.GRAYSCALE if c == 1 else image.RGB565
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img = image.Image(w, h, pixfmt, buffer=buffer)
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offset = len(buffer) - (w * h * (1 if c == 1 else 2))
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img = image.Image(w, h, pixfmt, buffer=memoryview(buffer)[offset:])
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# Copy and scale (if needed) the input image to the input buffer.
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hints = image.BILINEAR | image.CENTER | image.SCALE_ASPECT_EXPAND | image.BLACK_BACKGROUND
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img.draw_image(self._image, 0, 0, roi=self.roi, hint=hints)
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# Scale and convert the image to input tensor data.
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img.unpack(buffer, dtype, scale=self.scale, mean=self.mean, stdev=self.stdev)
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# Convert the image in-place into an ndarray input tensor.
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array = img.to_ndarray(dtype, buffer=buffer)
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# Normalize the input tensor.
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if dtype == ord('f'):
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fscale = (self.scale[1] - self.scale[0]) / 255.0
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fadd = self.scale[0]
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def grayscale(x):
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return (x[0] * 0.299) + (x[1] * 0.587) + (x[2] * 0.114)
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if c == 1:
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fadd = (fadd - grayscale(self.mean)) / grayscale(self.stdev)
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fscale = fscale / grayscale(self.stdev)
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else:
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fadd = (fadd - np.array(self.mean)) / np.array(self.stdev)
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fscale = fscale / np.array(self.stdev)
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array = (array * fscale) + fadd
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@ -423,95 +423,6 @@ void imlib_fill_image_from_float(image_t *img, int w, int h, float *data, float
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}
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}
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// Unpacks src into dst. dst must be an array of src->w*src->h*dtype*channels bytes, where channels is
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// 1 for grayscale and 3 for RGB.
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void imlib_unpack(void *dst, image_t *src, const char dtype, float *scale, float *mean, float *stdev) {
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// src will be unpacked into dst in reverse order so that we can handle in-place unpacking.
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int size = (src->w * src->h) - 1; // must be int per countdown loop
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float fscale = 1.0f, fadd = 0.0f;
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if (scale[0] == 0.0f && scale[1] == 1.0f) {
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fscale = 1.0f / 255.0f;
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} else if (scale[0] == -1.0f && scale[1] == 1.0f) {
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fscale = 2.0f / 255.0f;
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fadd = -1.0f;
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} else if (scale[0] == -128.0f && scale[1] == 127.0f) {
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fadd = -128.0f;
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}
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float fscale_r = fscale, fadd_r = fadd;
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float fscale_g = fscale, fadd_g = fadd;
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float fscale_b = fscale, fadd_b = fadd;
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// To normalize the input image we need to subtract the mean and divide by the standard deviation.
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// We can do this by applying the normalization to fscale and fadd outside the loop.
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// Red
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fadd_r = (fadd_r - mean[0]) / stdev[0];
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fscale_r /= stdev[0];
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// Green
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fadd_g = (fadd_g - mean[1]) / stdev[1];
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fscale_g /= stdev[1];
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// Blue
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fadd_b = (fadd_b - mean[2]) / stdev[2];
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fscale_b /= stdev[2];
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// Grayscale -> Y = 0.299R + 0.587G + 0.114B
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float m = (mean[0] * 0.299f) + (mean[1] * 0.587f) + (mean[2] * 0.114f);
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float s = (stdev[0] * 0.299f) + (stdev[1] * 0.587f) + (stdev[2] * 0.114f);
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fadd = (fadd - m) / s;
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fscale /= s;
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if (src->pixfmt == PIXFORMAT_GRAYSCALE) {
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uint8_t *input_u8 = (uint8_t *) src->data;
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if (dtype == 'f') {
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// convert u8 -> f32
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float *output_f32 = (float *) dst;
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for (; size >= 0; size -= 1) {
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output_f32[size] = (input_u8[size] * fscale) + fadd;
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}
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} else {
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// convert u8 -> s8
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#if (__ARM_ARCH > 6)
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uint32_t *input_u32 = (uint32_t *) src->data;
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uint32_t *output_u32 = (uint32_t *) dst;
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for (; size >= 3; size -= 4) {
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output_u32[size / 4] = input_u32[size / 4] ^ 0x80808080;
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}
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#endif
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uint8_t *input_u8 = (uint8_t *) src->data;
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uint8_t *output_u8 = (uint8_t *) dst;
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for (; size >= 0; size -= 1) {
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output_u8[size] = input_u8[size] ^ 128;
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}
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}
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} else if (src->pixfmt == PIXFORMAT_RGB565) {
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int rgb_size = size * 3; // must be int per countdown loop
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if (dtype == 'f') {
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uint16_t *input_u16 = (uint16_t *) src->data;
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float *output_f32 = (float *) dst;
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for (; size >= 0; size -= 1, rgb_size -= 3) {
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int pixel = input_u16[size];
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output_f32[rgb_size + 0] = (COLOR_RGB565_TO_R8(pixel) * fscale_r) + fadd_r;
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output_f32[rgb_size + 1] = (COLOR_RGB565_TO_G8(pixel) * fscale_g) + fadd_g;
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output_f32[rgb_size + 2] = (COLOR_RGB565_TO_B8(pixel) * fscale_b) + fadd_b;
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}
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} else {
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uint16_t *input_u16 = (uint16_t *) src->data;
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uint8_t *output_u8 = (uint8_t *) dst;
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for (; size >= 0; size -= 1, rgb_size -= 3) {
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int pixel = input_u16[size];
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output_u8[rgb_size + 0] = COLOR_RGB565_TO_R8(pixel) ^ 128;
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output_u8[rgb_size + 1] = COLOR_RGB565_TO_G8(pixel) ^ 128;
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output_u8[rgb_size + 2] = COLOR_RGB565_TO_B8(pixel) ^ 128;
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}
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}
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} else {
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mp_raise_msg(&mp_type_ValueError, MP_ERROR_TEXT("Expected input channels to be 1 or 3"));
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}
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}
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int8_t imlib_rgb565_to_l(uint16_t pixel) {
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float r_lin = xyz_table[COLOR_RGB565_TO_R8(pixel)];
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float g_lin = xyz_table[COLOR_RGB565_TO_G8(pixel)];
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@ -1157,7 +1157,6 @@ void imlib_deinit_all();
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// Generic Helper Functions
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void imlib_fill_image_from_float(image_t *img, int w, int h, float *data, float min, float max,
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bool mirror, bool flip, bool dst_transpose, bool src_transpose);
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void imlib_unpack(void *dst, image_t *src, const char dtype, float *scale, float *mean, float *stdev);
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// Bayer Image Processing
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pixformat_t imlib_bayer_shift(pixformat_t pixfmt, int x, int y, bool transpose);
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@ -725,22 +725,19 @@ static mp_obj_t py_image_bytearray(mp_obj_t img_obj) {
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}
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static MP_DEFINE_CONST_FUN_OBJ_1(py_image_bytearray_obj, py_image_bytearray);
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static mp_obj_t py_image_unpack(uint n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
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enum { ARG_buffer, ARG_dtype, ARG_scale, ARG_mean, ARG_stdev };
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#if defined(MODULE_ULAB_ENABLED) && (ULAB_MAX_DIMS == 4)
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static mp_obj_t py_image_to_ndarray(uint n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
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enum { ARG_dtype, ARG_buffer };
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static const mp_arg_t allowed_args[] = {
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{ MP_QSTR_buffer, MP_ARG_OBJ | MP_ARG_REQUIRED, {.u_rom_obj = MP_ROM_NONE} },
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{ MP_QSTR_dtype, MP_ARG_OBJ | MP_ARG_REQUIRED, {.u_rom_obj = MP_ROM_NONE } },
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{ MP_QSTR_scale, MP_ARG_OBJ | MP_ARG_KW_ONLY, {.u_rom_obj = MP_ROM_NONE } },
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{ MP_QSTR_mean, MP_ARG_OBJ | MP_ARG_KW_ONLY, {.u_rom_obj = MP_ROM_NONE } },
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{ MP_QSTR_stdev, MP_ARG_OBJ | MP_ARG_KW_ONLY, {.u_rom_obj = MP_ROM_NONE } },
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{ MP_QSTR_buffer, MP_ARG_OBJ | MP_ARG_KW_ONLY, {.u_rom_obj = MP_ROM_NONE} },
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};
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image_t *image = py_helper_arg_to_image(pos_args[0], ARG_IMAGE_ANY);
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mp_arg_val_t args[MP_ARRAY_SIZE(allowed_args)];
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mp_arg_parse_all(n_args - 1, pos_args + 1, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
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mp_buffer_info_t bufinfo = {0};
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mp_get_buffer_raise(args[ARG_buffer].u_obj, &bufinfo, MP_BUFFER_WRITE);
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int len = image->w * image->h;
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int dtype_code;
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int dtype_size;
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@ -753,7 +750,6 @@ static mp_obj_t py_image_unpack(uint n_args, const mp_obj_t *pos_args, mp_map_t
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}
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switch (dtype_code) {
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case 'c':
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case 'b':
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case 'B': {
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dtype_size = 1;
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@ -769,14 +765,24 @@ static mp_obj_t py_image_unpack(uint n_args, const mp_obj_t *pos_args, mp_map_t
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}
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}
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size_t shape[ULAB_MAX_DIMS];
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size_t strides[ULAB_MAX_DIMS];
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int channels;
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int ndim;
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switch (image->pixfmt) {
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case PIXFORMAT_GRAYSCALE: {
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memcpy(shape, (size_t []) {0, 0, image->h, image->w}, sizeof(shape));
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memcpy(strides, (size_t []) {0, 0, image->w * dtype_size, dtype_size}, sizeof(strides));
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channels = 1;
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ndim = 2;
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break;
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}
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case PIXFORMAT_RGB565: {
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memcpy(shape, (size_t []) {0, image->h, image->w, 3}, sizeof(shape));
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memcpy(strides, (size_t []) {0, image->w * dtype_size * 3, dtype_size * 3, dtype_size}, sizeof(strides));
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channels = 3;
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ndim = 3;
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break;
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}
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default: {
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@ -785,24 +791,78 @@ static mp_obj_t py_image_unpack(uint n_args, const mp_obj_t *pos_args, mp_map_t
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}
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}
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if ((image->w * image->h * dtype_size * channels) > bufinfo.len) {
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mp_raise_ValueError(MP_ERROR_TEXT("Buffer size is too small"));
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ndarray_obj_t *ndarray;
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if (args[ARG_buffer].u_obj != mp_const_none) {
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mp_buffer_info_t bufinfo = {0};
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mp_get_buffer_raise(args[ARG_buffer].u_obj, &bufinfo, MP_BUFFER_WRITE);
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if ((len * dtype_size * channels) > bufinfo.len) {
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mp_raise_ValueError(MP_ERROR_TEXT("Buffer is too small"));
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}
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ndarray = m_new_obj(ndarray_obj_t);
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ndarray->base.type = &ulab_ndarray_type;
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ndarray->dtype = dtype_code;
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ndarray->boolean = NDARRAY_NUMERIC;
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ndarray->ndim = ndim;
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ndarray->len = len * channels;
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ndarray->itemsize = dtype_size;
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memcpy(ndarray->shape, shape, sizeof(shape));
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memcpy(ndarray->strides, strides, sizeof(strides));
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ndarray->array = bufinfo.buf;
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ndarray->origin = bufinfo.buf;
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} else {
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ndarray = ndarray_new_dense_ndarray(ndim, shape, dtype_code);
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}
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// scale, offset
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float scale[2] = {0.0f, 1.0f};
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py_helper_arg_to_float_array(args[ARG_scale].u_obj, scale, 2);
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int shift = (dtype_code == 'b') ? 0x80808080 : 0x00000000;
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float mean[3] = {0.0f, 0.0f, 0.0f};
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py_helper_arg_to_float_array(args[ARG_mean].u_obj, mean, 3);
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if (image->pixfmt == PIXFORMAT_GRAYSCALE) {
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uint8_t *input_u8 = (uint8_t *) image->data;
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if (dtype_code == 'f') {
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float *output_f32 = (float *) ndarray->array;
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for (int i = 0; i < len; i++) {
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output_f32[i] = input_u8[i];
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}
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} else {
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uint8_t *output_u8 = (uint8_t *) ndarray->array;
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float stdev[3] = {1.0f, 1.0f, 1.0f};
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py_helper_arg_to_float_array(args[ARG_stdev].u_obj, stdev, 3);
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int i = 0;
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imlib_unpack(bufinfo.buf, image, dtype_code, scale, mean, stdev);
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return pos_args[0];
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for (; i < len; i += 4) {
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*((uint32_t *) (output_u8 + i)) = *((uint32_t *) (input_u8 + i)) ^ shift;
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}
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for (; i < len; i++) {
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output_u8[i] = input_u8[i] ^ shift;
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}
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}
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} else {
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uint16_t *input_u16 = (uint16_t *) image->data;
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if (dtype_code == 'f') {
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float *output_f32 = (float *) ndarray->array;
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for (int i = 0, j = 0; i < len; i++, j += 3) {
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int pixel = input_u16[i];
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output_f32[j + 0] = COLOR_RGB565_TO_R8(pixel);
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output_f32[j + 1] = COLOR_RGB565_TO_G8(pixel);
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output_f32[j + 2] = COLOR_RGB565_TO_B8(pixel);
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}
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} else {
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uint8_t *output_u8 = (uint8_t *) ndarray->array;
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for (int i = 0, j = 0; i < len; i++, j += 3) {
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int pixel = input_u16[i];
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output_u8[j + 0] = COLOR_RGB565_TO_R8(pixel) ^ shift;
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output_u8[j + 1] = COLOR_RGB565_TO_G8(pixel) ^ shift;
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output_u8[j + 2] = COLOR_RGB565_TO_B8(pixel) ^ shift;
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}
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}
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}
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return MP_OBJ_FROM_PTR(ndarray);
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}
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static MP_DEFINE_CONST_FUN_OBJ_KW(py_image_unpack_obj, 1, py_image_unpack);
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static MP_DEFINE_CONST_FUN_OBJ_KW(py_image_to_ndarray_obj, 1, py_image_to_ndarray);
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#endif
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static mp_obj_t py_image_get_pixel(uint n_args, const mp_obj_t *args, mp_map_t *kw_args) {
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image_t *arg_img = py_helper_arg_to_image(args[0], ARG_IMAGE_UNCOMPRESSED);
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@ -6469,7 +6529,9 @@ static const mp_rom_map_elem_t locals_dict_table[] = {
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{MP_ROM_QSTR(MP_QSTR_format), MP_ROM_PTR(&py_image_format_obj)},
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{MP_ROM_QSTR(MP_QSTR_size), MP_ROM_PTR(&py_image_size_obj)},
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{MP_ROM_QSTR(MP_QSTR_bytearray), MP_ROM_PTR(&py_image_bytearray_obj)},
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{MP_ROM_QSTR(MP_QSTR_unpack), MP_ROM_PTR(&py_image_unpack_obj)},
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#if defined(MODULE_ULAB_ENABLED) && (ULAB_MAX_DIMS == 4)
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{MP_ROM_QSTR(MP_QSTR_to_ndarray), MP_ROM_PTR(&py_image_to_ndarray_obj)},
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#endif
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{MP_ROM_QSTR(MP_QSTR_get_pixel), MP_ROM_PTR(&py_image_get_pixel_obj)},
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{MP_ROM_QSTR(MP_QSTR_set_pixel), MP_ROM_PTR(&py_image_set_pixel_obj)},
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{MP_ROM_QSTR(MP_QSTR_to_bitmap), MP_ROM_PTR(&py_image_to_bitmap_obj)},
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