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Update app.py
Browse filesshow system info
app.py
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@@ -13,6 +13,11 @@ from mediapipe.framework.formats import landmark_pb2
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from mediapipe.tasks import python
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from mediapipe.tasks.python import vision
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import cv2
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from diffusers import (
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FlaxControlNetModel,
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@@ -210,7 +215,22 @@ def infer(prompt, negative_prompt, image, model_type="Standard"):
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images = images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:])
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results = [i for i in images]
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with gr.Blocks(theme='gradio/soft') as demo:
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@@ -301,7 +321,7 @@ with gr.Blocks(theme='gradio/soft') as demo:
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submit_btn = gr.Button(value = "Submit")
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# inputs = [prompt_input, negative_prompt, input_image]
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# submit_btn.click(fn=infer, inputs=inputs, outputs=[output_image])
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with gr.Column():
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output_image = gr.Gallery(label='Output Image', show_label=False, elem_id="gallery").style(grid=2, height='auto')
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@@ -334,12 +354,12 @@ with gr.Blocks(theme='gradio/soft') as demo:
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],
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],
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inputs=[prompt_input, negative_prompt, input_image, model_type],
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outputs=[output_image],
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fn=infer,
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cache_examples=True,
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)
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inputs = [prompt_input, negative_prompt, input_image, model_type]
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submit_btn.click(fn=infer, inputs=inputs, outputs=[output_image])
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demo.launch()
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from mediapipe.tasks import python
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from mediapipe.tasks.python import vision
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import cv2
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import psutil
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from gpuinfo import GPUInfo
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import time
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import gc
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import torch
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from diffusers import (
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FlaxControlNetModel,
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images = images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:])
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results = [i for i in images]
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# running info
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time_end = time.time()
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time_diff = time_end - time_start
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gc.collect()
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torch.cuda.empty_cache()
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memory = psutil.virtual_memory()
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gpu_utilization, gpu_memory = GPUInfo.gpu_usage()
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gpu_utilization = gpu_utilization[0] if len(gpu_utilization) > 0 else 0
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gpu_memory = gpu_memory[0] if len(gpu_memory) > 0 else 0
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system_info = f"""
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*Memory: {memory.total / (1024 * 1024 * 1024):.2f}GB, used: {memory.percent}%, available: {memory.available / (1024 * 1024 * 1024):.2f}GB.*
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*Processing time: {time_diff:.5} seconds.*
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*GPU Utilization: {gpu_utilization}%, GPU Memory: {gpu_memory}MiB.*
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"""
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return [overlap_image, annotated_image] + results, system_info
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with gr.Blocks(theme='gradio/soft') as demo:
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submit_btn = gr.Button(value = "Submit")
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# inputs = [prompt_input, negative_prompt, input_image]
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# submit_btn.click(fn=infer, inputs=inputs, outputs=[output_image])
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system_info = gr.Markdown(f"*Memory: {memory.total / (1024 * 1024 * 1024):.2f}GB, used: {memory.percent}%, available: {memory.available / (1024 * 1024 * 1024):.2f}GB*")
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with gr.Column():
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output_image = gr.Gallery(label='Output Image', show_label=False, elem_id="gallery").style(grid=2, height='auto')
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],
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],
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inputs=[prompt_input, negative_prompt, input_image, model_type],
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outputs=[output_image, system_info],
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fn=infer,
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cache_examples=True,
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)
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inputs = [prompt_input, negative_prompt, input_image, model_type]
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submit_btn.click(fn=infer, inputs=inputs, outputs=[output_image, system_info])
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demo.launch()
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