Open realcarlos opened 1 year ago
`from diffusers import DiffusionPipeline from diffusers.utils import pt_to_pil import torch
stage_1 = DiffusionPipeline.from_pretrained("DeepFloyd/IF-I-XL-v1.0", variant="fp16", torch_dtype=torch.float16) stage_1.enable_xformers_memory_efficient_attention() # remove line if torch.version >= 2.0.0 stage_1.enable_model_cpu_offload()
stage_2 = DiffusionPipeline.from_pretrained( "DeepFloyd/IF-II-L-v1.0", text_encoder=None, variant="fp16", torch_dtype=torch.float16 ) stage_2.enable_xformers_memory_efficient_attention() # remove line if torch.version >= 2.0.0 stage_2.enable_model_cpu_offload()
safety_modules = {"feature_extractor": stage_1.feature_extractor, "safety_checker": stage_1.safety_checker, "watermarker": stage_1.watermarker} stage_3 = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-x4-upscaler", **safety_modules, torch_dtype=torch.float16) stage_3.enable_xformers_memory_efficient_attention() # remove line if torch.version >= 2.0.0 stage_3.enable_model_cpu_offload()
prompt = 'a photo of a kangaroo wearing an orange hoodie and blue sunglasses standing in front of the eiffel tower holding a sign that says "very deep learning"'
prompt_embeds, negative_embeds = stage_1.encode_prompt(prompt)
generator = torch.manual_seed(0)
image = stage_1(prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_embeds, generator=generator, output_type="pt").images pt_to_pil(image)[0].save("./if_stage_I.png")
image = stage_2( image=image, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_embeds, generator=generator, output_type="pt" ).images pt_to_pil(image)[0].save("./if_stage_II.png")
image = stage_3(prompt=prompt, image=image, generator=generator, noise_level=100).images image[0].save("./if_stage_III.png")`
I got one picture like this:
but when I followed this code : `from deepfloyd_if.modules import IFStageI, IFStageII, StableStageIII from deepfloyd_if.modules.t5 import T5Embedder
device = 'cuda:0' if_I = IFStageI('IF-I-XL-v1.0', device=device) if_II = IFStageII('IF-II-L-v1.0', device=device) if_III = StableStageIII('stable-diffusion-x4-upscaler', device=device) t5 = T5Embedder(device="cpu") from deepfloyd_if.pipelines import dream
prompt = 'ultra close-up color photo portrait of rainbow owl with deer horns in the woods' count = 4
result = dream( t5=t5, if_I=if_I, if_II=if_II, if_III=if_III, prompt=[prompt]*count, seed=42, if_I_kwargs={ "guidance_scale": 7.0, "sample_timestep_respacing": "smart100", }, if_II_kwargs={ "guidance_scale": 4.0, "sample_timestep_respacing": "smart50", }, if_III_kwargs={ "guidance_scale": 9.0, "noise_level": 20, "sample_timestep_respacing": "75", }, )
if_III.show(result['III'], size=14) `
I just got this:
`from diffusers import DiffusionPipeline from diffusers.utils import pt_to_pil import torch
stage 1
stage_1 = DiffusionPipeline.from_pretrained("DeepFloyd/IF-I-XL-v1.0", variant="fp16", torch_dtype=torch.float16) stage_1.enable_xformers_memory_efficient_attention() # remove line if torch.version >= 2.0.0 stage_1.enable_model_cpu_offload()
stage 2
stage_2 = DiffusionPipeline.from_pretrained( "DeepFloyd/IF-II-L-v1.0", text_encoder=None, variant="fp16", torch_dtype=torch.float16 ) stage_2.enable_xformers_memory_efficient_attention() # remove line if torch.version >= 2.0.0 stage_2.enable_model_cpu_offload()
stage 3
safety_modules = {"feature_extractor": stage_1.feature_extractor, "safety_checker": stage_1.safety_checker, "watermarker": stage_1.watermarker} stage_3 = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-x4-upscaler", **safety_modules, torch_dtype=torch.float16) stage_3.enable_xformers_memory_efficient_attention() # remove line if torch.version >= 2.0.0 stage_3.enable_model_cpu_offload()
prompt = 'a photo of a kangaroo wearing an orange hoodie and blue sunglasses standing in front of the eiffel tower holding a sign that says "very deep learning"'
text embeds
prompt_embeds, negative_embeds = stage_1.encode_prompt(prompt)
generator = torch.manual_seed(0)
stage 1
image = stage_1(prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_embeds, generator=generator, output_type="pt").images pt_to_pil(image)[0].save("./if_stage_I.png")
stage 2
image = stage_2( image=image, prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_embeds, generator=generator, output_type="pt" ).images pt_to_pil(image)[0].save("./if_stage_II.png")
stage 3
image = stage_3(prompt=prompt, image=image, generator=generator, noise_level=100).images image[0].save("./if_stage_III.png")`
I got one picture like this:
but when I followed this code : `from deepfloyd_if.modules import IFStageI, IFStageII, StableStageIII from deepfloyd_if.modules.t5 import T5Embedder
device = 'cuda:0' if_I = IFStageI('IF-I-XL-v1.0', device=device) if_II = IFStageII('IF-II-L-v1.0', device=device) if_III = StableStageIII('stable-diffusion-x4-upscaler', device=device) t5 = T5Embedder(device="cpu") from deepfloyd_if.pipelines import dream
prompt = 'ultra close-up color photo portrait of rainbow owl with deer horns in the woods' count = 4
result = dream( t5=t5, if_I=if_I, if_II=if_II, if_III=if_III, prompt=[prompt]*count, seed=42, if_I_kwargs={ "guidance_scale": 7.0, "sample_timestep_respacing": "smart100", }, if_II_kwargs={ "guidance_scale": 4.0, "sample_timestep_respacing": "smart50", }, if_III_kwargs={ "guidance_scale": 9.0, "noise_level": 20, "sample_timestep_respacing": "75", }, )
if_III.show(result['III'], size=14) `
I just got this: