qnloft
/
ComfyUI
mirror of https://github.com/comfyanonymous/ComfyUI.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Make previews into cli option

This commit is contained in:
space-nuko 2023-06-05 13:19:02 -05:00
parent f326a0a468
commit 48f7ec750c
4 changed files with 58 additions and 85 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

36
comfy/cli_args.py
View File

@ -1,4 +1,35 @@
import argparse
import enum
class EnumAction(argparse.Action):
"""
Argparse action for handling Enums
"""
def __init__(self, **kwargs):
# Pop off the type value
enum_type = kwargs.pop("type", None)
# Ensure an Enum subclass is provided
if enum_type is None:
raise ValueError("type must be assigned an Enum when using EnumAction")
if not issubclass(enum_type, enum.Enum):
raise TypeError("type must be an Enum when using EnumAction")
# Generate choices from the Enum
choices = tuple(e.value for e in enum_type)
kwargs.setdefault("choices", choices)
kwargs.setdefault("metavar", f"[{','.join(list(choices))}]")
super(EnumAction, self).__init__(**kwargs)
self._enum = enum_type
def __call__(self, parser, namespace, values, option_string=None):
# Convert value back into an Enum
value = self._enum(values)
setattr(namespace, self.dest, value)
parser = argparse.ArgumentParser()
@ -13,6 +44,11 @@ parser.add_argument("--dont-upcast-attention", action="store_true", help="Disabl
parser.add_argument("--force-fp32", action="store_true", help="Force fp32 (If this makes your GPU work better please report it).")
parser.add_argument("--directml", type=int, nargs="?", metavar="DIRECTML_DEVICE", const=-1, help="Use torch-directml.")
class PreviewType(enum.Enum):
TAESD = "taesd"
parser.add_argument("--disable-previews", action="store_true", help="Disable showing node previews.")
parser.add_argument("--default-preview-method", type=str, default=PreviewType.TAESD, metavar="PREVIEW_TYPE", help="Default preview method for sampler nodes.")
attn_group = parser.add_mutually_exclusive_group()
attn_group.add_argument("--use-split-cross-attention", action="store_true", help="Use the split cross attention optimization instead of the sub-quadratic one. Ignored when xformers is used.")
attn_group.add_argument("--use-pytorch-cross-attention", action="store_true", help="Use the new pytorch 2.0 cross attention function.")

1
main.py
View File

@ -45,7 +45,6 @@ def hijack_progress(server):
server.send_sync("progress", { "value": value, "max": total}, server.client_id)
if preview_image_bytes is not None:
server.send_sync(BinaryEventTypes.PREVIEW_IMAGE, preview_image_bytes, server.client_id)
pass
comfy.utils.set_progress_bar_global_hook(hook)
def cleanup_temp():

104
nodes.py
View File

@ -24,6 +24,7 @@ import comfy.samplers
import comfy.sample
import comfy.sd
import comfy.utils
from comfy.cli_args import args
from comfy.taesd.taesd import TAESD
import comfy.clip_vision
@ -180,21 +181,6 @@ class VAEDecodeTiled:
def decode(self, vae, samples):
return (vae.decode_tiled(samples["samples"]), )
class TAESDDecode:
@classmethod
def INPUT_TYPES(s):
return {"required": { "samples": ("LATENT", ), "taesd": ("TAESD", )}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "decode"
CATEGORY = "latent"
def decode(self, taesd, samples):
device = comfy.model_management.get_torch_device()
# [B, C, H, W] -> [B, H, W, C]
pixels = taesd.decoder(samples["samples"].to(device)).permute(0, 2, 3, 1).detach().clamp(0, 1)
return (pixels, )
class VAEEncode:
@classmethod
def INPUT_TYPES(s):
@ -272,21 +258,6 @@ class VAEEncodeForInpaint:
return ({"samples":t, "noise_mask": (mask_erosion[:,:,:x,:y].round())}, )
class TAESDEncode:
@classmethod
def INPUT_TYPES(s):
return {"required": { "pixels": ("IMAGE", ), "taesd": ("TAESD", )}}
RETURN_TYPES = ("LATENT",)
FUNCTION = "encode"
CATEGORY = "latent"
def encode(self, taesd, pixels):
device = comfy.model_management.get_torch_device()
# [B, H, W, C] -> [B, C, H, W]
samples = taesd.encoder(pixels.permute(0, 3, 1, 2).to(device)).to(device)
return ({"samples": samples}, )
class TAESDPreviewerImpl(LatentPreviewer):
def __init__(self, taesd):
self.taesd = taesd
@ -297,18 +268,6 @@ class TAESDPreviewerImpl(LatentPreviewer):
x_sample = x_sample * 0.5
return x_sample
class TAESDPreviewer:
@classmethod
def INPUT_TYPES(s):
return {"required": { "taesd": ("TAESD", ), }}
RETURN_TYPES = ("LATENT_PREVIEWER",)
FUNCTION = "make_previewer"
CATEGORY = "latent/previewer"
def make_previewer(self, taesd):
return (TAESDPreviewerImpl(taesd), )
class SaveLatent:
def __init__(self):
self.output_dir = folder_paths.get_output_directory()
@ -524,26 +483,6 @@ class VAELoader:
vae = comfy.sd.VAE(ckpt_path=vae_path)
return (vae,)
class TAESDLoader:
@classmethod
def INPUT_TYPES(s):
model_list = folder_paths.get_filename_list("taesd")
return {"required": {
"encoder_name": (model_list, { "default": "taesd_encoder.pth" }),
"decoder_name": (model_list, { "default": "taesd_decoder.pth" })
}}
RETURN_TYPES = ("TAESD",)
FUNCTION = "load_taesd"
CATEGORY = "loaders"
def load_taesd(self, encoder_name, decoder_name):
device = comfy.model_management.get_torch_device()
encoder_path = folder_paths.get_full_path("taesd", encoder_name)
decoder_path = folder_paths.get_full_path("taesd", decoder_name)
taesd = TAESD(encoder_path, decoder_path).to(device)
return (taesd,)
class ControlNetLoader:
@classmethod
def INPUT_TYPES(s):
@ -1039,7 +978,7 @@ def decode_latent_to_preview_image(previewer, device, preview_format, x0):
return preview_bytes
def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False, previewer=None):
def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False):
device = comfy.model_management.get_torch_device()
latent_image = latent["samples"]
@ -1057,6 +996,17 @@ def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive,
if preview_format not in ["JPEG", "PNG"]:
preview_format = "JPEG"
previewer = None
if not args.disable_previews:
# TODO previewer methods
encoder_path = folder_paths.get_full_path("taesd", "taesd_encoder.pth")
decoder_path = folder_paths.get_full_path("taesd", "taesd_decoder.pth")
if encoder_path and decoder_path:
taesd = TAESD(encoder_path, decoder_path).to(device)
previewer = TAESDPreviewerImpl(taesd)
else:
print("Warning: TAESD previews enabled, but could not find models/taesd/taesd_encoder.pth and models/taesd/taesd_decoder.pth")
pbar = comfy.utils.ProgressBar(steps)
def callback(step, x0, x, total_steps):
preview_bytes = None
@ -1085,18 +1035,16 @@ class KSampler:
"negative": ("CONDITIONING", ),
"latent_image": ("LATENT", ),
"denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
},
"optional": {
"previewer": ("LATENT_PREVIEWER",)
}}
}
}
RETURN_TYPES = ("LATENT",)
FUNCTION = "sample"
CATEGORY = "sampling"
def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0, previewer=None):
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, previewer=previewer)
def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0):
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
class KSamplerAdvanced:
@classmethod
@ -1115,24 +1063,22 @@ class KSamplerAdvanced:
"start_at_step": ("INT", {"default": 0, "min": 0, "max": 10000}),
"end_at_step": ("INT", {"default": 10000, "min": 0, "max": 10000}),
"return_with_leftover_noise": (["disable", "enable"], ),
},
"optional": {
"previewer": ("LATENT_PREVIEWER",)
}}
}
}
RETURN_TYPES = ("LATENT",)
FUNCTION = "sample"
CATEGORY = "sampling"
def sample(self, model, add_noise, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, start_at_step, end_at_step, return_with_leftover_noise, denoise=1.0, previewer=None):
def sample(self, model, add_noise, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, start_at_step, end_at_step, return_with_leftover_noise, denoise=1.0):
force_full_denoise = True
if return_with_leftover_noise == "enable":
force_full_denoise = False
disable_noise = False
if add_noise == "disable":
disable_noise = True
return common_ksampler(model, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, disable_noise=disable_noise, start_step=start_at_step, last_step=end_at_step, force_full_denoise=force_full_denoise, previewer=previewer)
return common_ksampler(model, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, disable_noise=disable_noise, start_step=start_at_step, last_step=end_at_step, force_full_denoise=force_full_denoise)
class SaveImage:
def __init__(self):
@ -1391,10 +1337,6 @@ NODE_CLASS_MAPPINGS = {
"VAEEncode": VAEEncode,
"VAEEncodeForInpaint": VAEEncodeForInpaint,
"VAELoader": VAELoader,
"TAESDDecode": TAESDDecode,
"TAESDEncode": TAESDEncode,
"TAESDPreviewer": TAESDPreviewer,
"TAESDLoader": TAESDLoader,
"EmptyLatentImage": EmptyLatentImage,
"LatentUpscale": LatentUpscale,
"LatentUpscaleBy": LatentUpscaleBy,
@ -1449,8 +1391,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"CheckpointLoader": "Load Checkpoint (With Config)",
"CheckpointLoaderSimple": "Load Checkpoint",
"VAELoader": "Load VAE",
"TAESDLoader": "Load TAESD",
"TAESDPreviewer": "TAESD Previewer",
"LoraLoader": "Load LoRA",
"CLIPLoader": "Load CLIP",
"ControlNetLoader": "Load ControlNet Model",
@ -1473,8 +1413,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"SetLatentNoiseMask": "Set Latent Noise Mask",
"VAEDecode": "VAE Decode",
"VAEEncode": "VAE Encode",
"TAESDDecode": "TAESD Decode",
"TAESDEncode": "TAESD Encode",
"LatentRotate": "Rotate Latent",
"LatentFlip": "Flip Latent",
"LatentCrop": "Crop Latent",

2
web/scripts/app.js
View File

@ -382,7 +382,7 @@ export class ComfyApp {
this.images = output.images;
imagesChanged = true;
imgURLs = imgURLs.concat(output.images.map(params => {
return "/view?" + new URLSearchParams(src).toString() + app.getPreviewFormatParam();
return "/view?" + new URLSearchParams(params).toString() + app.getPreviewFormatParam();
}))
}
}