Spaces:
Paused
Paused
| import gradio as gr | |
| from urllib.parse import urlparse | |
| import requests | |
| import time | |
| import os | |
| from utils.gradio_helpers import parse_outputs, process_outputs | |
| inputs = [] | |
| inputs.append(gr.Video( | |
| label="Mp4" | |
| )) | |
| inputs.append(gr.Dropdown( | |
| choices=[2, 4, 8, 16, 32], label="framerate_multiplier", info='''Determines how many intermediate frames to generate between original frames. E.g., a value of 2 will double the frame rate, and 4 will quadruple it, etc.''', value="2" | |
| )) | |
| inputs.append(gr.Checkbox( | |
| label="Keep Original Duration", info='''Should the enhanced video retain the original duration? If set to `True`, the model will adjust the frame rate to maintain the video's original duration after adding interpolated frames. If set to `False`, the frame rate will be set based on `custom_fps`.''', value=True | |
| )) | |
| inputs.append(gr.Slider( | |
| label="Custom Fps", info='''Set `keep_original_duration` to `False` to use this! Desired frame rate (fps) for the enhanced video. This will only be considered if `keep_original_duration` is set to `False`.''', value=None, | |
| minimum=1, maximum=240 | |
| )) | |
| names = ['mp4', 'framerate_multiplier', 'keep_original_duration', 'custom_fps'] | |
| outputs = [] | |
| outputs.append(gr.Video()) | |
| outputs.append(gr.Video()) | |
| outputs.append(gr.Video()) | |
| expected_outputs = len(outputs) | |
| 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) | |
| difference_outputs = expected_outputs - len(processed_outputs) | |
| # If less outputs than expected, hide the extra ones | |
| if difference_outputs > 0: | |
| extra_outputs = [gr.update(visible=False)] * difference_outputs | |
| processed_outputs.extend(extra_outputs) | |
| # If more outputs than expected, cap the outputs to the expected number | |
| elif difference_outputs < 0: | |
| processed_outputs = processed_outputs[:difference_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}") | |
| title = "Demo for st-mfnet cog image by zsxkib" | |
| model_description = "📽️ Increase Framerate 🎬 ST-MFNet: A Spatio-Temporal Multi-Flow Network for Frame Interpolation" | |
| app = gr.Interface( | |
| fn=predict, | |
| inputs=inputs, | |
| outputs=outputs, | |
| title=title, | |
| description=model_description, | |
| allow_flagging="never", | |
| ) | |
| app.launch(share=True) | |