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import gradio as gr
import subprocess
import os
from PIL import Image
def resize_image(image_path, target_height, output_path):
# Open the image file
with Image.open(image_path) as img:
# Calculate the ratio to resize the image to the target height
ratio = target_height / float(img.size[1])
# Calculate the new width based on the aspect ratio
new_width = int(float(img.size[0]) * ratio)
# Resize the image
resized_img = img.resize((new_width, target_height), Image.LANCZOS)
# Save the resized image
resized_img.save(output_path)
return resized_img
def generate(image, prompt, seed):
print(image, prompt, seed)
image_path = os.path.splitext(image)[0]
image_name = os.path.basename(image_path)
resized=resize_image(image, 512, f"output/{image_name}.jpg")
print(f"IMAGE NAME: {image_name}")
command = f"python handrefiner.py --input_img {resized} --out_dir output --strength 0.55 --weights models/inpaint_depth_control.ckpt --prompt '{prompt}' --seed {seed}"
try:
result = subprocess.run(command, shell=True, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
output_path = 'output'
print("Output:", result.stdout)
print(output_path)
# List all files and directories in the given directory
contents = os.listdir("output")
# Print the contents
for item in contents:
print(item)
return f"output/{image_name}_0.jpg"
except subprocess.CalledProcessError as e:
print("Error:", e.stderr)
return None
css="""
#col-container{
max-width: 860px;
margin: 0 auto;
}
"""
with gr.Blocks() as demo:
with gr.Column(elem_id="col-container"):
gr.HTML("""
<h2 style="text-aligb: center;">
HandRefiner
</h2>
""")
with gr.Row():
with gr.Column():
image = gr.Image(type='filepath')
textbox = gr.Textbox(show_label=False, value="a person facing the camera, making a hand gesture, indoor")
seed = gr.Slider(label="Seed", minimum=0, maximum=1000000, value=643534)
button = gr.Button()
output_image = gr.Image(show_label=False, type="filepath", interactive=False, height=512, width=512)
button.click(fn=generate, inputs=[image, textbox, seed], outputs=[output_image])
demo.queue().launch(inline=False, share=True, debug=True) |