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import gradio as gr
import requests.exceptions
from huggingface_hub import HfApi, hf_hub_download
from huggingface_hub.repocard import metadata_load
def load_agent(model_id):
"""
This function load the agent's video and results
:return: video_path
"""
# Load the metrics
metadata = get_metadata(model_id)
# Get the accuracy
results = parse_metrics_accuracy(metadata)
# Load the video
video_path = hf_hub_download(model_id, filename="replay.mp4")
return video_path, results
def parse_metrics_accuracy(meta):
if "model-index" not in meta:
return None
result = meta["model-index"][0]["results"]
metrics = result[0]["metrics"]
accuracy = metrics[0]["value"]
return accuracy
def get_metadata(model_id):
"""
Get the metadata of the model repo
:param model_id:
:return: metadata
"""
try:
readme_path = hf_hub_download(model_id, filename="README.md")
metadata = metadata_load(readme_path)
print(metadata)
return metadata
except requests.exceptions.HTTPError:
return None
agent1 = gr.Interface(load_agent, gr.Textbox(
label="model_1",
), ["video", "text"])
agent2 = gr.Interface(load_agent, gr.Textbox(
label="model_2",
), ["video", "text"])
gr.Series(agent1, agent2).launch()
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