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Update app.py
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app.py
CHANGED
@@ -1,21 +1,6 @@
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import gradio as gr
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from transformers import pipeline
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from PIL import Image
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#import os
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def load_images_from_current_directory():
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images = []
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current_directory = os.getcwd()
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for filename in os.listdir(current_directory):
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if filename.endswith(".jpg") or filename.endswith(".png"):
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img_path = os.path.join(current_directory, filename)
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img = Image.open(img_path)
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if img is not None:
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images.append(img)
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return images
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# Example: Load images from the current directory
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#example_images = load_images_from_current_directory()
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# Define the image classification function
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def classify_image(image):
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@@ -57,11 +42,9 @@ article = "<p style='text-align: center'>Image Classification | Demo Model</p>"
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# Prepare examples with loaded images
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#for img in example_images:
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# examples.append([np.array(img), os.path.basename(os.path.splitext(img.filename)[0])])
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demo = gr.Interface(fn=classify_image, inputs=image, outputs=label, description=description, article=article, title=title)
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# Launch the Gradio interface
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demo.launch()
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import gradio as gr
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from transformers import pipeline
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from PIL import Image
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# Define the image classification function
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def classify_image(image):
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# Prepare examples with loaded images
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examples = ["Normal_0.jpg", "Normal_1.jpg", "Normal_2.jpg", "Tumor_0.jpg", "Tumor_1.jpg", "Tumor_2.jpg"]
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demo = gr.Interface(fn=classify_image, inputs=image, outputs=label, description=description, article=article, title=title, examples=examples)
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# Launch the Gradio interface
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demo.launch()
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