import gradio as gr from urllib.parse import urlparse import requests import time import os from utils.gradio_helpers import parse_outputs, process_outputs names = ['image', 'rotate_pitch', 'rotate_yaw', 'rotate_roll', 'blink', 'eyebrow', 'wink', 'pupil_x', 'pupil_y', 'aaa', 'eee', 'woo', 'smile', 'src_ratio', 'sample_ratio', 'crop_factor', 'output_format', 'output_quality'] def predict(request: gr.Request, *args, progress=gr.Progress(track_tqdm=True)): headers = {'Content-Type': 'application/json'} payload = {"input": {}} base_url = "http://0.0.0.0:7860" for i, key in enumerate(names): value = args[i] if value and (os.path.exists(str(value))): value = f"{base_url}/file=" + value if value is not None and value != "": payload["input"][key] = value response = requests.post("http://0.0.0.0:5000/predictions", headers=headers, json=payload) if response.status_code == 201: follow_up_url = response.json()["urls"]["get"] response = requests.get(follow_up_url, headers=headers) while response.json()["status"] != "succeeded": if response.json()["status"] == "failed": raise gr.Error("The submission failed!") response = requests.get(follow_up_url, headers=headers) time.sleep(1) if response.status_code == 200: json_response = response.json() #If the output component is JSON return the entire output response if(outputs[0].get_config()["name"] == "json"): return json_response["output"] predict_outputs = parse_outputs(json_response["output"]) processed_outputs = process_outputs(predict_outputs) return tuple(processed_outputs) if len(processed_outputs) > 1 else processed_outputs[0] else: if(response.status_code == 409): raise gr.Error(f"Sorry, the Cog image is still processing. Try again in a bit.") raise gr.Error(f"The submission failed! Error: {response.status_code}") with gr.Blocks() as demo: with gr.Column(): gr.Markdown("# Expression Editor") gr.Markdown("Demo for expression-editor cog image by fofr") gr.HTML("""

Duplicate this Space to skip the queue and enjoy faster inference on the GPU of your choice

""") with gr.Row(): with gr.Column(): image = gr.Image( label="Image", type="filepath" ) with gr.Column(): result_image = gr.Image() submit_btn = gr.Button("Submit") with gr.Row(): rotate_pitch = gr.Slider( label="Rotate Pitch", info='''Rotation pitch: Adjusts the up and down tilt of the face''', value=0, minimum=-20, maximum=20 ) rotate_yaw = gr.Slider( label="Rotate Yaw", info='''Rotation yaw: Adjusts the left and right turn of the face''', value=0, minimum=-20, maximum=20 ) rotate_roll = gr.Slider( label="Rotate Roll", info='''Rotation roll: Adjusts the tilt of the face to the left or right''', value=0, minimum=-20, maximum=20 ) with gr.Row(): blink = gr.Slider( label="Blink", info='''Blink: Controls the degree of eye closure''', value=0, minimum=-20, maximum=5 ) eyebrow = gr.Slider( label="Eyebrow", info='''Eyebrow: Adjusts the height and shape of the eyebrows''', value=0, minimum=-10, maximum=15 ) wink = gr.Slider( label="Wink", info='''Wink: Controls the degree of one eye closing''', value=0, minimum=0, maximum=25 ) pupil_x = gr.Slider( label="Pupil X", info='''Pupil X: Adjusts the horizontal position of the pupils''', value=0, minimum=-15, maximum=15 ) pupil_y = gr.Slider( label="Pupil Y", info='''Pupil Y: Adjusts the vertical position of the pupils''', value=0, minimum=-15, maximum=15 ) with gr.Row(): aaa = gr.Slider( label="Aaa", info='''AAA: Controls the mouth opening for 'aaa' sound''', value=0, minimum=-30, maximum=120 ) eee = gr.Slider( label="Eee", info='''EEE: Controls the mouth shape for 'eee' sound''', value=0, minimum=-20, maximum=15 ) woo = gr.Slider( label="Woo", info='''WOO: Controls the mouth shape for 'woo' sound''', value=0, minimum=-20, maximum=15 ) smile = gr.Slider( label="Smile", info='''Smile: Adjusts the degree of smiling''', value=0, minimum=-0.3, maximum=1.3 ) with gr.Accordion("More Settings", open=False): with gr.column(): with gr.Row(): src_ratio = gr.Number( label="Src Ratio", info='''Source ratio''', value=1 ) sample_ratio = gr.Slider( label="Sample Ratio", info='''Sample ratio''', value=1, minimum=-0.2, maximum=1.2 ) crop_factor = gr.Slider( label="Crop Factor", info='''Crop factor''', value=1.7, minimum=1.5, maximum=2.5 ) with gr.Row(): output_format = gr.Dropdown( choices=['webp', 'jpg', 'png'], label="output_format", info='''Format of the output images''', value="webp" ) output_quality = gr.Number( label="Output Quality", info='''Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.''', value=95 ) inputs = [image, rotate_pitch, rotate_yaw, rotate_roll, blink, eyebrow, wink, pupil_x, pupil_y, aaa, eee, woo, smile, src_ratio, sample_ratio, crop_factor, output_format, output_quality] outputs = [result_image] submit_btn.click( fn=predict, inputs=inputs, outputs=outputs, ) rotate_pitch.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") rotate_yaw.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") rotate_roll.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") blink.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") eyebrow.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") wink.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") pupil_x.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") pupil_y.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") aaa.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") eee.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") woo.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") smile.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal") demo.launch(share=False, show_error=True)