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Running
on
L40S
| 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}") | |
| css = ''' | |
| #top{position: fixed;} | |
| ''' | |
| with gr.Blocks() as demo: | |
| with gr.Column(): | |
| gr.Markdown("# Expression Editor") | |
| gr.Markdown("Demo for expression-editor cog image by fofr") | |
| with gr.Row(): | |
| with gr.Column(): | |
| image = gr.Image( | |
| label="Input image", | |
| type="filepath", | |
| height=180 | |
| ) | |
| with gr.Row(): | |
| rotate_pitch = gr.Slider( | |
| label="Rotate Up-Down", | |
| value=0, | |
| minimum=-20, maximum=20 | |
| ) | |
| rotate_yaw = gr.Slider( | |
| label="Rotate Left-Right turn", | |
| value=0, | |
| minimum=-20, maximum=20 | |
| ) | |
| rotate_roll = gr.Slider( | |
| label="Rotate Left-Right tilt", value=0, | |
| minimum=-20, maximum=20 | |
| ) | |
| with gr.Row(): | |
| blink = gr.Slider( | |
| label="Blink", value=0, | |
| minimum=-20, maximum=5 | |
| ) | |
| eyebrow = gr.Slider( | |
| label="Eyebrow", value=0, | |
| minimum=-10, maximum=15 | |
| ) | |
| wink = gr.Slider( | |
| label="Wink", value=0, | |
| minimum=0, maximum=25 | |
| ) | |
| with gr.Row(): | |
| pupil_x = gr.Slider( | |
| label="Pupil X", value=0, | |
| minimum=-15, maximum=15 | |
| ) | |
| pupil_y = gr.Slider( | |
| label="Pupil Y", value=0, | |
| minimum=-15, maximum=15 | |
| ) | |
| with gr.Row(): | |
| aaa = gr.Slider( | |
| label="Aaa", value=0, | |
| minimum=-30, maximum=120 | |
| ) | |
| eee = gr.Slider( | |
| label="Eee", value=0, | |
| minimum=-20, maximum=15 | |
| ) | |
| woo = gr.Slider( | |
| label="Woo", value=0, | |
| minimum=-20, maximum=15 | |
| ) | |
| smile = gr.Slider( | |
| label="Smile", value=0, | |
| minimum=-0.3, maximum=1.3 | |
| ) | |
| with gr.Accordion("More Settings", open=False): | |
| 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 | |
| ) | |
| 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 | |
| ) | |
| submit_btn = gr.Button("Submit") | |
| with gr.Column(): | |
| result_image = gr.Image(elem_id="top") | |
| gr.HTML(""" | |
| <div style="display: flex; justify-content: center; align-items: center; text-align: center;"> | |
| <p style="display: flex;gap: 6px;"> | |
| <a href="https://huggingface.co/spaces/fffiloni/expression-editor?duplicate=true"> | |
| <img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/duplicate-this-space-md.svg" alt="Duplicate this Space"> | |
| </a> to skip the queue and enjoy faster inference on the GPU of your choice | |
| </p> | |
| </div> | |
| """) | |
| 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) |