将数组更改为整数百分比值
Change an array to an integer percentage value
我有一个函数,当 运行 时,它以数组的形式给我一个值作为输出,但我需要输出作为结果片段的整数百分比
def pred_datsci(file_path):
prev_precompute = learn.precompute
learn.precompute = False
try:
trn_tfms, val_tfms = tfms_from_model(arch,sz)
test_img = open_image(file_path)
im = val_tfms(test_img)
pred = learn.predict_array(im[None])
class_index = (np.exp(pred))
class_index1 = np.argmax(np.exp(pred))
print(class_index*100)
return data.classes[class_index1]
finally:
learn.precompute = prev_precompute
这是输出的样子:
pred_datsci(f"data/dogscats1/valid/dogs/12501.jpg")
我的问题是如何让这两个值显示为:
猫 % = 15.81724%
狗 % = 84.18274%
您可以将 zip 函数用作:
for z in zip(['Cat', 'Dog'], [15.3, 84.6]):
print('%s %% = %s%%'%(z[0], z[1]))
我有一个函数,当 运行 时,它以数组的形式给我一个值作为输出,但我需要输出作为结果片段的整数百分比
def pred_datsci(file_path):
prev_precompute = learn.precompute
learn.precompute = False
try:
trn_tfms, val_tfms = tfms_from_model(arch,sz)
test_img = open_image(file_path)
im = val_tfms(test_img)
pred = learn.predict_array(im[None])
class_index = (np.exp(pred))
class_index1 = np.argmax(np.exp(pred))
print(class_index*100)
return data.classes[class_index1]
finally:
learn.precompute = prev_precompute
这是输出的样子:
pred_datsci(f"data/dogscats1/valid/dogs/12501.jpg")
我的问题是如何让这两个值显示为:
猫 % = 15.81724%
狗 % = 84.18274%
您可以将 zip 函数用作:
for z in zip(['Cat', 'Dog'], [15.3, 84.6]):
print('%s %% = %s%%'%(z[0], z[1]))