Spaces:
Sleeping
Sleeping
File size: 3,877 Bytes
d35f312 a0f2ea5 d35f312 f0e9ec4 d35f312 f0e9ec4 d35f312 4222b0d d35f312 4222b0d d35f312 f0e9ec4 d35f312 4222b0d d35f312 a0f2ea5 d35f312 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 |
import comet_ml
import uuid
import gradio as gr
DESCRIPTION = """Glad to see you here 😄.
You can use this Space to log predictions to [Comet](https://www.comet.ml/site) from Spaces that use Text to Image Diffusion Models.
Keep track of all your prompts and generated images so that you can easily find the good ones!
Set your Comet credentials in the Comet Settings tab, and select the Space you want to log predictions
from in the Diffusion Model tab
"""
class MyProject:
def __init__(self):
self.experiment = None
def start_experiment(
self, comet_api_key: str, comet_workspace: str, comet_project_name: str
):
if not comet_api_key:
return """
Please add your API key in order to log your predictions to a Comet Experiment.
If you don't have a Comet account yet, you can sign up using the link below:
[Sign Up for Comet](https://www.comet.ml/signup)
"""
else:
try:
self.experiment = comet_ml.Experiment(
api_key=comet_api_key,
workspace=comet_workspace,
project_name=comet_project_name,
)
self.experiment.add_tags(["spaces"])
return f"Started {self.experiment.name}. Happy logging!😊"
except Exception as e:
return e
def end_experiment(self):
if self.experiment is not None:
self.experiment.end()
return f"Ended {self.experiment.name}"
def get_experiment_status(self):
return f"Running {self.experiment.name}"
def start_comet_interface(self):
demo = gr.Blocks()
with demo:
# credentials
comet_api_key = gr.Textbox(label="Comet API Key")
comet_workspace = gr.Textbox(label="Comet Workspace")
comet_project_name = gr.Textbox(label="Comet Project Name")
with gr.Row():
start_experiment = gr.Button("Start Experiment", variant="primary")
status = gr.Button("Experiment Status")
end_experiment = gr.Button("End Experiment", variant="secondary")
output = gr.Markdown(label="Status")
start_experiment.click(
self.start_experiment,
inputs=[
comet_api_key,
comet_workspace,
comet_project_name,
],
outputs=output,
)
status.click(self.get_experiment_status, inputs=None, outputs=None)
end_experiment.click(self.end_experiment, inputs=None, outputs=output)
return demo
def predict(
self,
model,
prompt,
):
io = gr.Interface.load(model)
image = io(prompt)
if self.experiment is not None:
image_id = uuid.uuid4().hex
self.experiment.log_image(image, name=image_id)
self.experiment.log_text(
prompt, metadata={"image_id": image_id, "model": model}
)
return image
def load_interface(self):
model = gr.Textbox(label="Model", value="spaces/valhalla/glide-text2im")
prompt = gr.Textbox(label="Prompt")
outputs = gr.Image(label="Image")
interface = gr.Interface(
self.predict,
inputs=[model, prompt],
outputs=outputs,
examples=[["spaces/valhalla/glide-text2im", "An oil painting of a corgi"]],
description=DESCRIPTION,
)
return interface
def launch(self):
interface = gr.TabbedInterface(
[self.start_comet_interface(), self.load_interface()],
tab_names=["Comet Settings", "Diffusion Model"],
)
interface.launch()
MyProject().launch()
|