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af9e948
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Parent(s):
3ed97b9
upgrade to gradio blocks (#1)
Browse files- upgrade to gradio blocks (274546c2d9b7fbb87d302c2d76789da4d490ca33)
Co-authored-by: Abdullah Meda <[email protected]>
app.py
CHANGED
@@ -1,10 +1,10 @@
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import
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import re
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import gradio as gr
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from pathlib import Path
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from transformers import AutoTokenizer, AutoFeatureExtractor, VisionEncoderDecoderModel
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# Pattern to ignore all the text after 2 or more full stops
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regex_pattern = "[.]{2,}"
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@@ -19,6 +19,10 @@ def post_process(text):
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return text
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def predict(image, max_length=64, num_beams=4):
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pixel_values = feature_extractor(images=image, return_tensors="pt").pixel_values
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pixel_values = pixel_values.to(device)
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@@ -52,29 +56,29 @@ print("Loaded feature_extractor")
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tokenizer = AutoTokenizer.from_pretrained(model.decoder.name_or_path, use_fast=True)
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if model.decoder.name_or_path == "gpt2":
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tokenizer.pad_token = tokenizer.eos_token
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print("Loaded tokenizer")
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import os
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import re
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import torch
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import gradio as gr
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from transformers import AutoTokenizer, AutoFeatureExtractor, VisionEncoderDecoderModel
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# Pattern to ignore all the text after 2 or more full stops
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regex_pattern = "[.]{2,}"
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return text
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def set_example_image(example: list) -> dict:
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return gr.Image.update(value=example[0])
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def predict(image, max_length=64, num_beams=4):
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pixel_values = feature_extractor(images=image, return_tensors="pt").pixel_values
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pixel_values = pixel_values.to(device)
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tokenizer = AutoTokenizer.from_pretrained(model.decoder.name_or_path, use_fast=True)
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if model.decoder.name_or_path == "gpt2":
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tokenizer.pad_token = tokenizer.eos_token
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print("Loaded tokenizer")
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examples = [[f"examples/{filename}"] for filename in next(os.walk('examples'), (None, None, []))[2]]
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print(f"Loaded {len(examples)} example images")
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with gr.Blocks(css="#title { margin: 0 auto; padding: 25px 25px 25px 25px }") as poster2plot:
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with gr.Column():
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with gr.Row():
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gr.Markdown("# Poster2Plot: Upload a Movie/T.V show poster to generate a plot", elem_id='title')
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with gr.Row():
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with gr.Column():
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with gr.Row():
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input_image = gr.Image(label='Input Image', type='numpy')
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with gr.Row():
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submit_button = gr.Button(value="Submit", variant='primary')
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with gr.Column():
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plot = gr.Textbox(label="Plot")
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with gr.Row():
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example_images = gr.Dataset(components=[input_image], samples=examples)
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with gr.Row():
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gr.Markdown("Made by: [dk-crazydiv](https://twitter.com/kartik_godawat) and [dsr](https://twitter.com/dsr_ai)")
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submit_button.click(fn=predict, inputs=[input_image], outputs=[plot])
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example_images.click(fn=set_example_image, inputs=[example_images], outputs=example_images.components)
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poster2plot.launch()
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