def predict_spec(model, path):
temp_spec = os.path.join(result_dir, "temp.png")
tools.make_spec(path, temp_spec)
x_batch = np.ndarray((1, 3, model.insize, model.insize), dtype=np.float32)
y_batch = np.zeros((1, ), dtype=np.int32)
x_batch[0] = read_image(temp_spec)
return get_result(x_batch, y_batch, model)[0]
def predict_spec(model,path):
temp_spec = os.path.join(result_dir,"temp.png")
tools.make_spec(path,temp_spec)
x_batch = np.ndarray((1,3,model.insize,model.insize), dtype=np.float32)
y_batch = np.zeros((1,), dtype=np.int32)
x_batch[0] = read_image(temp_spec)
return get_result(x_batch,y_batch,model)[0]
def make_train():
#posi_tempo=[]
print "start positive music feature extract"
posi_mel=[]
posi_chroma=[]
posi_mfcc=[]
hi_res=0
#posi_tempo=[]
#nega_tempo=[]
with warnings.catch_warnings():
warnings.simplefilter("ignore")
for i in tqdm(positive_sample):
#tools.make_vec(os.path.join(posi_dir,i),0,(posi_mel,posi_mfcc,posi_chroma))
try:
mel,mfcc,chroma = tools.get_feature(os.path.join(posi_dir,i))
mel=[(0,j) for j in mel]
mfcc=[(0,j) for j in mfcc]
chroma=[(0,j) for j in chroma]
posi_mel+=mel
posi_mfcc+=mfcc
posi_chroma+=chroma
tools.make_spec(os.path.join(posi_dir,i),os.path.join(data_dir,"posi_spectro",i[:-3]+"png"))
except audioop.error:
hi_res+=1
p_dump(posi_mel,"posi_mel")
p_dump(posi_mfcc,"posi_mfcc")
p_dump(posi_chroma,"posi_chroma")
del posi_mel
del posi_mfcc
del posi_chroma
print "start negative music feature extract"
nega_mel=[]
nega_chroma=[]
nega_mfcc=[]
for i in tqdm(negative_sample):
#tools.make_vec(os.path.join(nega_dir,i),0,(nega_mel,nega_mfcc,nega_chroma))
try:
mel,mfcc,chroma=tools.get_feature(os.path.join(nega_dir,i))
mel=[(1,j) for j in mel]
mfcc=[(1,j) for j in mfcc]
chroma=[(1,j) for j in chroma]
nega_mel+=mel
nega_mfcc+=mfcc
nega_chroma+=chroma
tools.make_spec(os.path.join(nega_dir,i),os.path.join(data_dir,"nega_spectro",i[:-3]+"png"))
except audioop.error:
hi_res+=1
p_dump(nega_mel,"nega_mel")
p_dump(nega_mfcc,"nega_mfcc")
p_dump(nega_chroma,"nega_chroma")
if hi_res:
print "{} files are not used.it may be 24bit.".format(hi_res)
def make_train():
#posi_tempo=[]
print "start positive music feature extract"
posi_mel = []
posi_chroma = []
posi_mfcc = []
hi_res = 0
#posi_tempo=[]
#nega_tempo=[]
with warnings.catch_warnings():
warnings.simplefilter("ignore")
for i in tqdm(positive_sample):
#tools.make_vec(os.path.join(posi_dir,i),0,(posi_mel,posi_mfcc,posi_chroma))
try:
mel, mfcc, chroma = tools.get_feature(os.path.join(
posi_dir, i))
mel = [(0, j) for j in mel]
mfcc = [(0, j) for j in mfcc]
chroma = [(0, j) for j in chroma]
posi_mel += mel
posi_mfcc += mfcc
posi_chroma += chroma
tools.make_spec(
os.path.join(posi_dir, i),
os.path.join(data_dir, "posi_spectro", i[:-3] + "png"))
except audioop.error:
hi_res += 1
p_dump(posi_mel, "posi_mel")
p_dump(posi_mfcc, "posi_mfcc")
p_dump(posi_chroma, "posi_chroma")
del posi_mel
del posi_mfcc
del posi_chroma
print "start negative music feature extract"
nega_mel = []
nega_chroma = []
nega_mfcc = []
for i in tqdm(negative_sample):
#tools.make_vec(os.path.join(nega_dir,i),0,(nega_mel,nega_mfcc,nega_chroma))
try:
mel, mfcc, chroma = tools.get_feature(os.path.join(
nega_dir, i))
mel = [(1, j) for j in mel]
mfcc = [(1, j) for j in mfcc]
chroma = [(1, j) for j in chroma]
nega_mel += mel
nega_mfcc += mfcc
nega_chroma += chroma
tools.make_spec(
os.path.join(nega_dir, i),
os.path.join(data_dir, "nega_spectro", i[:-3] + "png"))
except audioop.error:
hi_res += 1
p_dump(nega_mel, "nega_mel")
p_dump(nega_mfcc, "nega_mfcc")
p_dump(nega_chroma, "nega_chroma")
if hi_res:
print "{} files are not used.it may be 24bit.".format(hi_res)
