Spaces:
Sleeping
Sleeping
File size: 1,793 Bytes
caae3e0 3afe20e caae3e0 2337a39 6bf7cb4 2337a39 cc1887c ff3f385 778806f 3bfbec3 72d2777 3bfbec3 6bc3d42 0814097 31ac16a 64e1a19 0814097 64e1a19 a77c349 6f76811 b7b5d68 cc1887c caae3e0 64e1a19 0bb8b0b a77c349 64e1a19 a77c349 64e1a19 caae3e0 a77c349 |
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 |
import gradio as gr
import numpy as np
from huggingface_hub import InferenceClient
client = InferenceClient("models/microsoft/trocr-base-handwritten")
def sepia(input_img):
sepia_filter = np.array([
[0.393, 0.769, 0.189],
[0.349, 0.686, 0.168],
[0.272, 0.534, 0.131]
])
sepia_img = input_img.dot(sepia_filter.T)
sepia_img /= sepia_img.max()
sepia_values = repr(sepia_img)
return sepia_img, sepia_values
## https://www.gradio.app/docs/gradio/blocks
## required positional arguments: 'inputs' and 'outputs'
def process_image(image):
# Your image processing logic here
return "Processed Text"
def additional_input(text):
return f"Additional input received: {text}"
sepia_interface = gr.Interface(sepia, gr.Image(), "image")
with gr.Blocks() as generated_output:
with gr.Column():
gr.Interface(fn=sepia,
inputs=gr.Image(),
outputs="image",
show_progress="minimal")
with gr.Row():
sepia_values_text=gr.Textbox(label="Sepia Values")
gr.Interface(sepia, outputs = "sepia_values_text")
#with gr.Blocks() as generated_output:
# inp = gr.Interface(sepia, gr.Image(), "image")
# out = gr.Textbox()
#demo = gr.TabbedInterface([sepia_interface, generated_output], ["RGB Sepia Filter", "Handwritten to Text"])
#with gr.Blocks() as demo:
# with gr.Row():
# input_img = gr.Image(label="Input Image")
# submit_button = gr.Button("Submit")
# output_img = gr.Image(label="Output Image")
# sepia_values_text = gr.Textbox(label="Sepia Values")
# submit_button.click(sepia, inputs=input_img, outputs=[output_img, sepia_values_text])
if __name__ == "__main__":
generated_output.launch()
|