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c042949 |
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from langhchain_generate_components import maker_wikipedia_chain
from utils import (
save_file, convert_obj_to_stl,
change_file_extension,
)
from mesh_utils import generate_mesh_images
from gradio_client import Client
def main():
# the object to be generated
query = "A Microscope"
# using a retriever we generat a list of Components
output = maker_wikipedia_chain.invoke(query)
# the first item
shap_e_sample = output['Material'][0]
client = Client("hysts/Shap-E")
result = client.predict(
shap_e_sample, # str in 'Prompt' Textbox component
1621396601, # float (numeric value between 0 and 2147483647) in 'Seed' Slider component
15, # float (numeric value between 1 and 20) in 'Guidance scale' Slider component
64, # float (numeric value between 2 and 100) in 'Number of inference steps' Slider component
api_name="/text-to-3d"
)
saved_file_name = "sample.glb"
# save to local machine
save_file(result,saved_file_name)
stl_file_location = change_file_extension(
saved_file_name,
".stl"
)
# convert into a stl without the texture
# as it is easiest to handle
convert_obj_to_stl(
result,
stl_file_location,
)
# Need to generate screenshot for the item
viewing_angles = [(30, 45), (60, 90), (45, 135)]
generate_mesh_images(
stl_file_location,
viewing_angles
)
# These screenshots need to be given to GPT-V
# for feedback
print(result)
x = 0
if __name__ == "__main__":
main() |