def test_full_integral_image_correctness():
''' Test generated full integral image correctness,
note that this relies on the corectness of interpreter and reference.py '''
block_size = (20, 20)
size = tuple(x*3 for x in block_size)
# generate random test image
test_image = [[float(random.randint(0, 255)) for i in xrange(size[0])] for j in xrange(size[1])]
# reference implementation
integral_ref = reference.gen_integral_image(test_image)
sq_integral_ref = reference.gen_integral_squared_image(test_image)
# pointer config
buffer_size = block_size[0]*block_size[1]
src_ptr = 0
integral_ptr = buffer_size
sq_integral_ptr = 2*buffer_size
# set up interpreter for integral image calculation
pe_dim = [s//b for s, b in zip(size, block_size)]
def code_gen(code, block_size, args):
return gen_code.gen_full_integral_image(code, src_ptr, integral_ptr, sq_integral_ptr, pe_dim, block_size)
code = Code()
code.set_generator(optimiser_wrapper(code_gen), block_size)
sim = Interpreter(code, test_image, block_size)
sim.run()
# get result of simulator with scaling, truncation turned off and float output
integral_test = sim.gen_output_image(1, False, False, True)
sq_integral_test = sim.gen_output_image(2, False, False, True)
# comparison of reference with blip sim
integral_err = compare_images(integral_ref, integral_test)
sq_integral_err = compare_images(sq_integral_ref, sq_integral_test)
err_eps = 0.001
if not ((integral_err < err_eps) and (sq_integral_err < err_eps)):
print 'integral comp:', integral_err
print 'squared integral comp:', sq_integral_err
print 'rendering instruction stream to file, can take a while'
try:
f = open('unoptimised_full_integral_image_trace.txt', 'w')
def tag_str(instr): return ', '.join(instr.tag) if hasattr(instr, 'tag') else ''
f.write('\n'.join(str(x).ljust(40) + ' tags: ' + tag_str(x) for x in code_gen(Code())))
f.close()
optim_gen = optimiser_wrapper(code_gen, block_size, {})
f = open('bad_full_integral_image_trace.txt', 'w')
def tag_str(instr): return ', '.join(instr.tag) if hasattr(instr, 'tag') else ''
f.write('\n'.join(str(x).ljust(40) + ' tags: ' + tag_str(x) for x in optim_gen(Code())))
f.close()
except Exception, e:
print 'could render instruction stream to file'
print 'err: ' + str(e)
assert False
def run_test(image, position, shape, block_size):
def code_gen(code, block_size, args):
return gen_code.gen_fullintegral_sum(code, code.r(4), position, shape, ptr, block_size)
code = Code()
code.set_generator(optimiser_wrapper(code_gen), block_size)
sim = Interpreter(code, image, block_size)
sim.run()
# extract value
return sim.procs[0][0].get_reg_by_name('r4')
def run_test(image, position, shape, block_size): code = Code() out_reg = code.alloc_reg() def code_gen(code, block_size, args): return gen_code.gen_integral_sum(code, out_reg, position, shape, ptr, block_size) code.set_generator(optimiser_wrapper(code_gen), block_size) sim = Interpreter(code, image, block_size) sim.run() # extract value return sim.procs[0][0].get_reg_by_name(str(out_reg))
def run_test(image, position, shape, ptr, block_size):
px, py = position
x, y, w, h = shape
xx = px + x
yy = py + y
points = ((xx, yy), (xx+w-1, yy), (xx, yy+h-1), (xx+w-1, yy+h-1))
def code_gen(code, block_size, args):
return gen_code.gen_fullintegral_sum2_2(code, code.r(4), ptr, points, block_size)
code = Code()
code.set_generator(optimiser_wrapper(code_gen), block_size)
sim = Interpreter(code, image, block_size)
sim.run()
# extract value
return sim.procs[0][0].get_reg_by_name('r4')
def gen_integral_image_correctness(): ''' test if generated integral image is correct, note that this relies on the corectness of interpreter and reference.py ''' # size = (120, 80) # block_size = (40, 40) size = (80, 80) block_size = size # generate random test image test_image = [[float(random.randint(0, 255)) for i in xrange(size[0])] for j in xrange(size[1])] # reference implementation integral_ref = reference.gen_integral_image(test_image) sq_integral_ref = reference.gen_integral_squared_image(test_image) # pointer config buffer_size = block_size[0]*block_size[1] src_ptr = 0 integral_ptr = buffer_size sq_integral_ptr = 2*buffer_size # set up interpreter for integral image calculation def code_gen(code, block_size, args): return gen_code.gen_integral_image(code, src_ptr, integral_ptr, sq_integral_ptr, block_size) code = Code() code.set_generator(optimiser_wrapper(code_gen), block_size) sim = Interpreter(code, test_image, block_size) sim.run() # get result of simulator with scaling, truncation turned off and float output integral_test = sim.gen_output_image(1, False, False, True) sq_integral_test = sim.gen_output_image(2, False, False, True) # comparison of reference with blip sim integral_err = compare_images(integral_ref, integral_test) sq_integral_err = compare_images(sq_integral_ref, sq_integral_test) err_eps = 0.001 if not ((integral_err < err_eps) and (sq_integral_err < err_eps)): print 'integral comp:', integral_err print 'squared integral comp:', sq_integral_err assert False
def run_test(codegen_function, image, cascade, block_size):
print 'running %s'%codegen_function.__name__
print 'XXX histogram equalisation is not implemented yet, use violajones impl'
print ' before executing simulator'
image = reference.equalizeHist(image)
width, height = block_size
pe_dim = (len(image[0])//width, len(image)//height)
args = {'haar_classifier': cascade, 'pe_dim':pe_dim}
# now execute the codegen
code = Code()
code.set_generator(optimiser_wrapper(codegen_function), block_size, args)
sim = Interpreter(code, image, block_size, 4)
sim.run()
detections_pixmap = sim.gen_output_image(1) # result is saved in first buffer
# convert the number of rejections in the stages to detections
detections = gen_code.convert_pixelmap_to_detections(detections_pixmap, cascade.size)
return detections
def run_test(position, integral_test, sq_integral_test, haar_size, block_size): integral_ptr = 0 sq_integral_ptr = block_size[0]*block_size[1] code = Code() out_reg = code.alloc_reg() def code_gen(code, block_size, args): return gen_code.gen_calc_variance(code, out_reg, position, integral_ptr, sq_integral_ptr, haar_size, block_size) code.set_generator(optimiser_wrapper(code_gen), block_size) sim = Interpreter(code, integral_test, block_size) # hack: in order to avoid calculating integral images, inject random values into the sq_integral buffer # this is easy since their is only a single PE for i, row in enumerate(sq_integral_test): for j, v in enumerate(row): sim.procs[0][0].memory.set(sq_integral_ptr + len(row)*i+j, v) sim.run() pe = sim.procs[0][0] # extract value return (1./(pe.get_reg_by_name(str(out_reg)))), pe
