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#[allow(unused_imports)]
use crate::prelude::*;
#[allow(unused_imports)]
use serde::{Deserialize, Serialize};
#[allow(unused_imports)]
use std::collections::HashMap;
#[derive(Debug, Serialize, Deserialize, Default)]
pub struct AnimateDiffV2VInput {
/// Base model to use for animation generation.
#[serde(skip_serializing_if = "Option::is_none")]
pub base_model: Option<String>,
/// The CFG (Classifier Free Guidance) scale is a measure of how close you want
/// the model to stick to your prompt when looking for a related image to show you.
#[serde(skip_serializing_if = "Option::is_none")]
pub guidance_scale: Option<f64>,
/// The list of LoRA weights to use.
#[serde(skip_serializing_if = "Option::is_none")]
pub loras: Option<Vec<Option<LoraWeight>>>,
/// The negative prompt to use. Use it to address details that you don't want
/// in the image. This could be colors, objects, scenery and even the small details
/// (e.g. moustache, blurry, low resolution).
#[serde(skip_serializing_if = "Option::is_none")]
pub negative_prompt: Option<String>,
/// Increasing the amount of steps tells Stable Diffusion that it should take more steps
/// to generate your final result which can increase the amount of detail in your image.
#[serde(skip_serializing_if = "Option::is_none")]
pub num_inference_steps: Option<i64>,
/// The prompt to use for generating the image. Be as descriptive as possible for best results.
/// "masterpiece, best quality, rocket in space, galaxies in the background"
pub prompt: String,
/// The same seed and the same prompt given to the same version of Stable Diffusion
/// will output the same image every time.
/// 537306
#[serde(skip_serializing_if = "Option::is_none")]
pub seed: Option<i64>,
/// Select every Nth frame from the video.
/// This can be used to reduce the number of frames to process, which can reduce the time and the cost.
/// However, it can also reduce the quality of the final video.
#[serde(skip_serializing_if = "Option::is_none")]
pub select_every_nth_frame: Option<i64>,
/// URL of the video.
/// "https://storage.googleapis.com/falserverless/model_tests/animatediff_v2v/rocket.mp4"
pub video_url: String,
}
#[derive(Debug, Serialize, Deserialize, Default)]
pub struct AnimateDiffV2VOutput {
/// Seed used for generating the video.
pub seed: i64,
pub timings: Timings,
/// Generated video file.
/// {"content_type":"video/mp4","url":"https://storage.googleapis.com/falserverless/model_tests/animatediff_v2v/turbo-rocket-output.mp4"}
pub video: File,
}
#[derive(Debug, Serialize, Deserialize, Default)]
pub struct AnimateDiffV2VTurboInput {
/// The CFG (Classifier Free Guidance) scale is a measure of how close you want
/// the model to stick to your prompt when looking for a related image to show you.
#[serde(skip_serializing_if = "Option::is_none")]
pub guidance_scale: Option<f64>,
/// The list of LoRA weights to use.
#[serde(skip_serializing_if = "Option::is_none")]
pub loras: Option<Vec<Option<LoraWeight>>>,
/// The negative prompt to use. Use it to address details that you don't want
/// in the image. This could be colors, objects, scenery and even the small details
/// (e.g. moustache, blurry, low resolution).
#[serde(skip_serializing_if = "Option::is_none")]
pub negative_prompt: Option<String>,
/// Increasing the amount of steps tells Stable Diffusion that it should take more steps
/// to generate your final result which can increase the amount of detail in your image.
#[serde(skip_serializing_if = "Option::is_none")]
pub num_inference_steps: Option<i64>,
/// The prompt to use for generating the image. Be as descriptive as possible for best results.
/// "masterpiece, best quality, rocket in space, galaxies in the background"
pub prompt: String,
/// The same seed and the same prompt given to the same version of Stable Diffusion
/// will output the same image every time.
/// 537306
#[serde(skip_serializing_if = "Option::is_none")]
pub seed: Option<i64>,
/// Select every Nth frame from the video.
/// This can be used to reduce the number of frames to process, which can reduce the time and the cost.
/// However, it can also reduce the quality of the final video.
#[serde(skip_serializing_if = "Option::is_none")]
pub select_every_nth_frame: Option<i64>,
/// URL of the video.
/// "https://storage.googleapis.com/falserverless/model_tests/animatediff_v2v/rocket.mp4"
pub video_url: String,
}
#[derive(Debug, Serialize, Deserialize)]
pub struct AnimateDiffV2VTurboOutput {
/// Seed used for generating the video.
pub seed: i64,
pub timings: Timings,
/// Generated video file.
/// {"content_type":"video/mp4","url":"https://storage.googleapis.com/falserverless/model_tests/animatediff_v2v/rocket-output.mp4"}
pub video: File,
}
#[derive(Debug, Serialize, Deserialize, Default)]
pub struct File {
/// The mime type of the file.
/// "image/png"
#[serde(skip_serializing_if = "Option::is_none")]
pub content_type: Option<String>,
/// File data
#[serde(skip_serializing_if = "Option::is_none")]
pub file_data: Option<String>,
/// The name of the file. It will be auto-generated if not provided.
/// "z9RV14K95DvU.png"
#[serde(skip_serializing_if = "Option::is_none")]
pub file_name: Option<String>,
/// The size of the file in bytes.
/// 4404019
#[serde(skip_serializing_if = "Option::is_none")]
pub file_size: Option<i64>,
/// The URL where the file can be downloaded from.
pub url: String,
}
#[derive(Debug, Serialize, Deserialize, Default)]
pub struct HTTPValidationError {
#[serde(skip_serializing_if = "Option::is_none")]
pub detail: Option<Vec<Option<ValidationError>>>,
}
#[derive(Debug, Serialize, Deserialize, Default)]
pub struct LoraWeight {
/// URL or the path to the LoRA weights. Or HF model name.
/// "https://civitai.com/api/download/models/135931"
/// "https://filebin.net/3chfqasxpqu21y8n/my-custom-lora-v1.safetensors"
pub path: String,
/// The scale of the LoRA weight. This is used to scale the LoRA weight
/// before merging it with the base model.
#[serde(skip_serializing_if = "Option::is_none")]
pub scale: Option<f64>,
}
#[derive(Debug, Serialize, Deserialize, Default)]
pub struct ValidationError {
pub loc: Vec<serde_json::Value>,
pub msg: String,
#[serde(rename = "type")]
pub ty: String,
}
#[derive(Debug, Serialize, Deserialize, Default)]
pub struct Timings {
#[serde(skip_serializing_if = "Option::is_none")]
#[serde(rename = "type")]
pub ty: Option<serde_json::Value>,
}
/// AnimateDiff Video-to-Video Evolved
///
/// Category: video-to-video
/// Machine Type: A100
pub fn turbo(
params: AnimateDiffV2VTurboInput,
) -> FalRequest<AnimateDiffV2VTurboInput, AnimateDiffV2VTurboOutput> {
FalRequest::new("fal-ai/animatediff-v2v/turbo", params)
}