flatyplus 0.1.0

a simple program to become content creator

Flaty Plus python package

introducing a program to become a content creator

What content can be created?

• Clipper YouTube
• Image generator (by AI)
• Interpolation frame
• Video maker

How to Use

Install flatyplus

Installing first flatyplus

!pip install flatyplus==0.1.0

Clipper YouTube

Clip only audio

from flatyplus import YTclip
YTclip.audio(
    "https://youtu.be/eIEgeaYJbN0", #youtube url
    clip=None,                      #trim video by specific time in tupple (start, end)=> ("00:00:00", "00:00:15")
    output=None                     #rename output
)

Clip only video

from flatyplus import YTclip
YTclip.video(
    "https://youtu.be/eIEgeaYJbN0", #youtube url
    short=False,                    #specific yt video type. res video if short True max-width<=1280 or False max-height<=1280
    clip=None,                      #trim video by specific time in tupple (start, end)=> ("00:00:00", "00:00:15")
    output=None                     #rename output
)

Clip audio and video

from flatyplus import YTclip
YTclip.audiovideo(
    "https://youtu.be/eIEgeaYJbN0", #youtube url
    short=False,                    #specific yt video type. res video if short True max-width<=1280 or False max-height<=1280
    clip=None,                      #trim video by specific time in tupple (start, end)=> ("00:00:00", "00:00:15")
    output=None                     #rename output
)

Image generator by AI

Dance cover by AI is only use sdxl model from diffuser hugging face. you can search model on here

Without Controlnet

Step 1. Instaling model

from flatyplus import sdxl_diffuser
sdxl_diffuser.init(
    "cagliostrolab/animagine-xl-3.1", #model from hugging face
    )

step 1.5. Add lora (optional)

sdxl_diffuser.lora(
    "nerijs/pixel-art-xl",  #lora model from hugging face
    weight_name=None,       #name of lora (name.safetensors)
    fuse=False              #if true lora will be fusing in to base model
    )

step 2. Generated image

img = sdxl_diffuser.image(
    "a girl width tourch",    #prompt
    (1024, 1024),             #size tuple (width, height)
    negative_prompt="",       #negative prompt
    seed=None,                #seed if None is random
    guidance_scale=7,         #guidance scale
    num_inference_steps=28,   #num inference steps
    output=None               #rename output if None is not saving the image
    )                               #returning image object

img

With controlnet

Step 1. Instaling model

from flatyplus import sdxl_diffuser
sdxl_diffuser.init(
    "cagliostrolab/animagine-xl-3.1", #model from hugging face
    control_mode=[]                 #controlnet mode in list available value are "canny", "openpose", "zoe-depth", "scribble"
    )

step 1.5. Add lora (optional)

sdxl_diffuser.lora(
    "nerijs/pixel-art-xl",  #lora model from hugging face
    weight_name=None,       #name of lora (name.safetensors)
    fuse=False              #if true lora will be fusing in to base model
    )

step 2. Generated image

img = sdxl_diffuser.image(
    "a girl width tourch",    #prompt
    (1024, 1024),             #size tuple (width, height)
    path=[],                  #list control image path length as control_mode above
    negative_prompt="",       #negative prompt
    seed=None,                #seed if None is random
    guidance_scale=7,         #guidance scale
    num_inference_steps=28,   #num inference steps
    output=None               #rename output if None is not saving the image
    )                         #returning image object

img

Interpolation frame

from flatyplus import interframe
interframe.interpolate(
    "",         #path that contain list of image (png) named in number (0.png -> n.png)
    num=2,      #num more higher more much generate frame
    loop=False, #true if want last back image to first image
    output      #rename output
    )

video maker

video write from image

from flatyplus import video
video.write(
    "path",          #path that contain list of image (png) named in number (0.png -> n.png)
    duration=5,      #duration of length video output
    resize=None,     #resize video resolution in tupple => (760, 1280)
    soundpath=None,  #path including sound in video
    background=None, #background color in hex/rgb or path image
    output=None      #rename output
    )

video clip

from flatyplus import video
video.clip(
    "video.mp4",       #video path
    start="00:00:00",  #start time by hh:mm:ss
    end="00:00:00",    #end time by hh:mm:ss
    crop=None,         #crop if is tuple (width, height), if is list [{"start":"hh:mm:ss", "duration": seconds, "crop":(width, height)}]
    resize=None,       #resize video
    output=None        #output rename
    )

video loop

from flatyplus import video
video.loop(
    "video.mp4",      #video path
    "3",              #how many time will be loop
    output=None       #output rename
    )

About me

A streamer, clippers, animator, content creator, pro gamer, programmer, story teller and bla bla bla ...

Anyway. Hello guys... My name is Flatyplus. I create this program just for my hobby. Hope you enjoy what im doing.

Im welcome to you to being my friends. Contact me if you have any help for me.

support me on SociaBuzz

https://sociabuzz.com/flatyplus/tribe