ONE - On-device Neural Engine
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jpeg2hdf5.py File Reference

Go to the source code of this file.

Namespaces

namespace  jpeg2hdf5
 

Variables

str jpeg2hdf5.helpstr
 
list jpeg2hdf5.supported_frameworks = ['tfl', 'caf']
 
dict jpeg2hdf5.args = {}
 
 jpeg2hdf5.argc = len(sys.argv)
 
 jpeg2hdf5.arg = sys.argv[i]
 
dict jpeg2hdf5.fw = args['-f']
 
dict jpeg2hdf5.indirname = args['-t']
 
str jpeg2hdf5.inputname = 'data'
 
 jpeg2hdf5.nproc
 
 jpeg2hdf5.proc_num
 
dict jpeg2hdf5.remove_existing = args['-r']
 
dict jpeg2hdf5.gen_binary = args['-b']
 
 jpeg2hdf5.testcases = glob.glob(indirname + '/testcase*/')
 
int jpeg2hdf5.number = 0
 
 jpeg2hdf5.infilename = glob.glob(testcase + 'input/*.JPEG')
 
str jpeg2hdf5.outfilename = testcase + 'input/' + infilename.split('/')[-1] + '.hdf5'
 
str jpeg2hdf5.binoutfilename = testcase + 'input/' + infilename.split('/')[-1] + '.dat'
 
int jpeg2hdf5.found_hdf = 0
 
int jpeg2hdf5.found_bin = 0
 
 jpeg2hdf5.h = im.size[0]
 
 jpeg2hdf5.w = im.size[1]
 
 jpeg2hdf5.s = im.split()
 
 jpeg2hdf5.r = s[0]
 
 jpeg2hdf5.g = s[0]
 
 jpeg2hdf5.b = s[0]
 
 jpeg2hdf5.rf = r.convert('F')
 
 jpeg2hdf5.gf = g.convert('F')
 
 jpeg2hdf5.bf = b.convert('F')
 
 jpeg2hdf5.rfb = rf.tobytes()
 
 jpeg2hdf5.gfb = gf.tobytes()
 
 jpeg2hdf5.bfb = bf.tobytes()
 
bool jpeg2hdf5.made_hdf = False
 
 jpeg2hdf5.reds = np.fromstring(rfb, count=(h * w), dtype='float32')
 
 jpeg2hdf5.greens = np.fromstring(gfb, count=(h * w), dtype='float32')
 
 jpeg2hdf5.blues = np.fromstring(bfb, count=(h * w), dtype='float32')
 
tuple jpeg2hdf5.dset_shape = (1, h, w, 3)
 
 jpeg2hdf5.narr = np.ndarray(shape=(0))
 
list jpeg2hdf5.mixed_ch = []
 
 jpeg2hdf5.dset = f.require_dataset(inputname, dset_shape, dtype='>f4')
 
 jpeg2hdf5.l = narr.tolist()