noise=np.random.normal(0,1,(100,100))# 使用生成器生成图像 generated_images=generator.predict(noise)# 可视化生成的图像 fig,axs=plt.subplots(10,10,figsize=(10,10),sharex=True,sharey=True)cnt=0foriinrange(10):forjinrange(10):axs[i,j].imshow(generated_images[cnt,:,:,0],cmap='gray'...
Or in Python: importqrcodeimportqrcode.image.svgifmethod=='basic':# Simple factory, just a set of rects.factory=qrcode.image.svg.SvgImageelifmethod=='fragment':# Fragment factory (also just a set of rects)factory=qrcode.image.svg.SvgFragmentImageelse:# Combined path factory, fixes white...
pythonminecraftminecraft-skinaimlpython3easy-to-usepowerfulminecraft-skinsgoogle-colabai-imagestable-diffusionai-image-generationai-image-generator UpdatedDec 31, 2024 Jupyter Notebook AI Image Generation Discord Bot @ pollinations.ai 🌸Used in 500+ servers ...
class ImageDataGenerator(object): 代码语言:javascript 代码运行次数:0 运行 AI代码解释 """Generate batchesoftensor image datawithreal-time data augmentation.The data will be loopedover(inbatches). 这个类是做什么用的?通过实时数据增强生成张量图像数据批次,并且可以循环迭代,我们知道在Keras中,当数据量很多...
validation_data=valigen,#验证数据集generatorvalidation_steps=128,#这个与验证数据集的batch_size也是一样,乘起来大于等于验证数据集个数callbacks=[callback] )forfileinfiles: pat=filepath+'/tmp/test-horse-or-human/testdata/'+file#img=cv2.imdecode(np.fromfile(pat,dtype=np.uint8),-1)img=image.lo...
import ipywidgets as widgets from IPython.display import display, clear_output import time class ImageGeneratorApp: def __init__(self): # 创建 UI 组件 self.prompt_input = widgets.Textarea( value='', placeholder='描述您想要生成的图像...', description='提示词:', disabled=False, layout=widg...
def__iter__(self)->Iterator[int]:n=len(self.data_source)ifself.generatorisNone:seed=int(torch.empty((),dtype=torch.int64).random_().item())generator=torch.Generator()generator.manual_seed(seed)else:generator=self.generatorifself.replacement:...else:for_inrange(self.num_samples//n):yield...
• datagen = ImageDataGenerator( • rotation_range=40, • width_shift_range=0.2, • height_shift_range=0.2, • shear_range=0.2, • zoom_range=0.2, • horizontal_flip=True, • fill_mode='nearest') • • gener=datagen.flow_from_directory(r'E:\C3D_Data\trian',#类别子...
在生成真实图像方面,常用的都是无监督模型,如GAN,VAE等。 然而ICCV2017的这篇文章,同样是从图像(图像分割结果的语义标注图)到原始的街景图像的转换,它并没有依靠生成对抗网络(GAN)以训练generator与discriminator network的方式来做image-to-image,而是采用了一种级联精练网络Cascaded Refinement Network (CRN)来实现逼...
Hash Generator (Independent Publisher) Hashify (Independent Publisher) Hashtag API (Independent Publisher) Have I Been Pwned (Independent Publisher) HelloSign HHS Media Services (Independent Publisher) HighGear Workflow Highspot HipChat HitHorizons HiveCPQ Product Configurator Holopin Honeywell Forge Host.io...