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import gradio as gr | |
import bpy | |
import tempfile | |
def enable_GPUS(): | |
bpy.data.scenes[0].render.engine = "CYCLES" #"CYCLES" | |
# Set the device_type | |
bpy.context.preferences.addons[ | |
"cycles" | |
].preferences.compute_device_type = "CUDA" # or "OPENCL" | |
# Set the device and feature set | |
bpy.context.scene.cycles.device = "GPU" | |
for scene in bpy.data.scenes: | |
scene.cycles.device = "GPU" | |
bpy.context.preferences.addons["cycles"].preferences.get_devices() | |
print(bpy.context.preferences.addons["cycles"].preferences.compute_device_type) | |
for d in bpy.context.preferences.addons["cycles"].preferences.devices: | |
d["use"] = True # Using all devices, include GPU and CPU | |
print(d["name"]) | |
def generate(): | |
with tempfile.NamedTemporaryFile(suffix=".JPEG", delete=False) as f: | |
bpy.context.scene.render.resolution_y = 200 | |
bpy.context.scene.render.resolution_x = 400 | |
bpy.context.scene.render.image_settings.file_format = "JPEG" | |
bpy.context.scene.render.filepath = f.name | |
enable_GPUS() | |
bpy.ops.render.render(animation=False, write_still=True) | |
bpy.data.images["Render Result"].save_render( | |
filepath=bpy.context.scene.render.filepath | |
) | |
bpy.app.handlers.render_stats.clear() | |
return f.name | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
with gr.Column(): | |
render_btn = gr.Button("Render") | |
with gr.Column(scale=3): | |
image = gr.Image(type="filepath") | |
render_btn.click( | |
generate, | |
outputs=[image], | |
) | |
demo.queue(concurrency_count=1) | |
demo.launch(debug=True, inline=True) | |
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