| from hume import HumeBatchClient
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| from hume.models.config import FaceConfig
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| import gradio as gr
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| def HumeBatch(client_key, file):
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| newTimeOut = 3000
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| client = HumeBatchClient(client_key, timeout=newTimeOut)
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| files = [file]
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| configs = [FaceConfig(identify_faces=True)]
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| job = client.submit_job(urls=[], configs=configs, files=files)
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| print(job)
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| print("Running...")
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| job.await_complete()
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| job.download_predictions("predictions.json")
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| job.download_artifacts("artifacts.zip")
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| return (job, job.get_predictions())
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| interface = gr.Interface(
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| fn = HumeBatch,
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| inputs = ["text", gr.Image(label = "Image to analyze", type="filepath")],
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| outputs = ["text", "text"],
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| description = "Enter a picture for emotion analysis"
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| ).launch(share=True, auth=("jet", "pass"), auth_message="check your email for username and password")
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