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Running
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Zero
File size: 8,458 Bytes
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from __future__ import annotations
import torch
from enum import Enum
from typing import Optional, Union
from pydantic import BaseModel, Field, confloat
class LumaIO:
LUMA_REF = "LUMA_REF"
LUMA_CONCEPTS = "LUMA_CONCEPTS"
class LumaReference:
def __init__(self, image: torch.Tensor, weight: float):
self.image = image
self.weight = weight
def create_api_model(self, download_url: str):
return LumaImageRef(url=download_url, weight=self.weight)
class LumaReferenceChain:
def __init__(self, first_ref: LumaReference=None):
self.refs: list[LumaReference] = []
if first_ref:
self.refs.append(first_ref)
def add(self, luma_ref: LumaReference=None):
self.refs.append(luma_ref)
def create_api_model(self, download_urls: list[str], max_refs=4):
if len(self.refs) == 0:
return None
api_refs: list[LumaImageRef] = []
for ref, url in zip(self.refs, download_urls):
api_ref = LumaImageRef(url=url, weight=ref.weight)
api_refs.append(api_ref)
return api_refs
def clone(self):
c = LumaReferenceChain()
for ref in self.refs:
c.add(ref)
return c
class LumaConcept:
def __init__(self, key: str):
self.key = key
class LumaConceptChain:
def __init__(self, str_list: list[str] = None):
self.concepts: list[LumaConcept] = []
if str_list is not None:
for c in str_list:
if c != "None":
self.add(LumaConcept(key=c))
def add(self, concept: LumaConcept):
self.concepts.append(concept)
def create_api_model(self):
if len(self.concepts) == 0:
return None
api_concepts: list[LumaConceptObject] = []
for concept in self.concepts:
if concept.key == "None":
continue
api_concepts.append(LumaConceptObject(key=concept.key))
if len(api_concepts) == 0:
return None
return api_concepts
def clone(self):
c = LumaConceptChain()
for concept in self.concepts:
c.add(concept)
return c
def clone_and_merge(self, other: LumaConceptChain):
c = self.clone()
for concept in other.concepts:
c.add(concept)
return c
def get_luma_concepts(include_none=False):
concepts = []
if include_none:
concepts.append("None")
return concepts + [
"truck_left",
"pan_right",
"pedestal_down",
"low_angle",
"pedestal_up",
"selfie",
"pan_left",
"roll_right",
"zoom_in",
"over_the_shoulder",
"orbit_right",
"orbit_left",
"static",
"tiny_planet",
"high_angle",
"bolt_cam",
"dolly_zoom",
"overhead",
"zoom_out",
"handheld",
"roll_left",
"pov",
"aerial_drone",
"push_in",
"crane_down",
"truck_right",
"tilt_down",
"elevator_doors",
"tilt_up",
"ground_level",
"pull_out",
"aerial",
"crane_up",
"eye_level"
]
class LumaImageModel(str, Enum):
photon_1 = "photon-1"
photon_flash_1 = "photon-flash-1"
class LumaVideoModel(str, Enum):
ray_2 = "ray-2"
ray_flash_2 = "ray-flash-2"
ray_1_6 = "ray-1-6"
class LumaAspectRatio(str, Enum):
ratio_1_1 = "1:1"
ratio_16_9 = "16:9"
ratio_9_16 = "9:16"
ratio_4_3 = "4:3"
ratio_3_4 = "3:4"
ratio_21_9 = "21:9"
ratio_9_21 = "9:21"
class LumaVideoOutputResolution(str, Enum):
res_540p = "540p"
res_720p = "720p"
res_1080p = "1080p"
res_4k = "4k"
class LumaVideoModelOutputDuration(str, Enum):
dur_5s = "5s"
dur_9s = "9s"
class LumaGenerationType(str, Enum):
video = 'video'
image = 'image'
class LumaState(str, Enum):
queued = "queued"
dreaming = "dreaming"
completed = "completed"
failed = "failed"
class LumaAssets(BaseModel):
video: Optional[str] = Field(None, description='The URL of the video')
image: Optional[str] = Field(None, description='The URL of the image')
progress_video: Optional[str] = Field(None, description='The URL of the progress video')
class LumaImageRef(BaseModel):
'''Used for image gen'''
url: str = Field(..., description='The URL of the image reference')
weight: confloat(ge=0.0, le=1.0) = Field(..., description='The weight of the image reference')
class LumaImageReference(BaseModel):
'''Used for video gen'''
type: Optional[str] = Field('image', description='Input type, defaults to image')
url: str = Field(..., description='The URL of the image')
class LumaModifyImageRef(BaseModel):
url: str = Field(..., description='The URL of the image reference')
weight: confloat(ge=0.0, le=1.0) = Field(..., description='The weight of the image reference')
class LumaCharacterRef(BaseModel):
identity0: LumaImageIdentity = Field(..., description='The image identity object')
class LumaImageIdentity(BaseModel):
images: list[str] = Field(..., description='The URLs of the image identity')
class LumaGenerationReference(BaseModel):
type: str = Field('generation', description='Input type, defaults to generation')
id: str = Field(..., description='The ID of the generation')
class LumaKeyframes(BaseModel):
frame0: Optional[Union[LumaImageReference, LumaGenerationReference]] = Field(None, description='')
frame1: Optional[Union[LumaImageReference, LumaGenerationReference]] = Field(None, description='')
class LumaConceptObject(BaseModel):
key: str = Field(..., description='Camera Concept name')
class LumaImageGenerationRequest(BaseModel):
prompt: str = Field(..., description='The prompt of the generation')
model: LumaImageModel = Field(LumaImageModel.photon_1, description='The image model used for the generation')
aspect_ratio: Optional[LumaAspectRatio] = Field(LumaAspectRatio.ratio_16_9, description='The aspect ratio of the generation')
image_ref: Optional[list[LumaImageRef]] = Field(None, description='List of image reference objects')
style_ref: Optional[list[LumaImageRef]] = Field(None, description='List of style reference objects')
character_ref: Optional[LumaCharacterRef] = Field(None, description='The image identity object')
modify_image_ref: Optional[LumaModifyImageRef] = Field(None, description='The modify image reference object')
class LumaGenerationRequest(BaseModel):
prompt: str = Field(..., description='The prompt of the generation')
model: LumaVideoModel = Field(LumaVideoModel.ray_2, description='The video model used for the generation')
duration: Optional[LumaVideoModelOutputDuration] = Field(None, description='The duration of the generation')
aspect_ratio: Optional[LumaAspectRatio] = Field(None, description='The aspect ratio of the generation')
resolution: Optional[LumaVideoOutputResolution] = Field(None, description='The resolution of the generation')
loop: Optional[bool] = Field(None, description='Whether to loop the video')
keyframes: Optional[LumaKeyframes] = Field(None, description='The keyframes of the generation')
concepts: Optional[list[LumaConceptObject]] = Field(None, description='Camera Concepts to apply to generation')
class LumaGeneration(BaseModel):
id: str = Field(..., description='The ID of the generation')
generation_type: LumaGenerationType = Field(..., description='Generation type, image or video')
state: LumaState = Field(..., description='The state of the generation')
failure_reason: Optional[str] = Field(None, description='The reason for the state of the generation')
created_at: str = Field(..., description='The date and time when the generation was created')
assets: Optional[LumaAssets] = Field(None, description='The assets of the generation')
model: str = Field(..., description='The model used for the generation')
request: Union[LumaGenerationRequest, LumaImageGenerationRequest] = Field(..., description="The request used for the generation")
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