Update app.py

app.py

@@ -149,140 +149,4 @@ with gr.Blocks() as demo:
     )
 
 # Start the application
-demo.launch(inline=False)
-
-
-
-
-# from fastai.vision.all import *
-# import gradio as gr
-# import fal_client
-# from PIL import Image
-# import io
-# import random
-# import requests
-# from pathlib import Path
-# import os
-
-# # Set FAL API key
-# os.environ["FAL_KEY"] = "19df8993-16d5-4561-a2f9-4649eff073e8:4b8330590d437063b9825805957694c5"
-
-# # Plant names and their Wikipedia links
-# search_terms_wikipedia = {
-#     "blazing star": "https://en.wikipedia.org/wiki/Mentzelia",
-#     "bristlecone pine": "https://en.wikipedia.org/wiki/Pinus_longaeva",
-#     "california bluebell": "https://en.wikipedia.org/wiki/Phacelia_minor",
-#     "california buckeye": "https://en.wikipedia.org/wiki/Aesculus_californica",
-#     "california buckwheat": "https://en.wikipedia.org/wiki/Eriogonum_fasciculatum",
-#     "california fuchsia": "https://en.wikipedia.org/wiki/Epilobium_canum",
-#     "california checkerbloom": "https://en.wikipedia.org/wiki/Sidalcea_malviflora",
-#     "california lilac": "https://en.wikipedia.org/wiki/Ceanothus",
-#     "california poppy": "https://en.wikipedia.org/wiki/Eschscholzia_californica",
-#     "california sagebrush": "https://en.wikipedia.org/wiki/Artemisia_californica",
-#     "california wild grape": "https://en.wikipedia.org/wiki/Vitis_californica",
-#     "california wild rose": "https://en.wikipedia.org/wiki/Rosa_californica",
-#     "coyote mint": "https://en.wikipedia.org/wiki/Monardella",
-#     "elegant clarkia": "https://en.wikipedia.org/wiki/Clarkia_unguiculata",
-#     "baby blue eyes": "https://en.wikipedia.org/wiki/Nemophila_menziesii",
-#     "hummingbird sage": "https://en.wikipedia.org/wiki/Salvia_spathacea",
-#     "delphinium": "https://en.wikipedia.org/wiki/Delphinium",
-#     "matilija poppy": "https://en.wikipedia.org/wiki/Romneya_coulteri",
-#     "blue-eyed grass": "https://en.wikipedia.org/wiki/Sisyrinchium_bellum",
-#     "penstemon spectabilis": "https://en.wikipedia.org/wiki/Penstemon_spectabilis",
-#     "seaside daisy": "https://en.wikipedia.org/wiki/Erigeron_glaucus",
-#     "sticky monkeyflower": "https://en.wikipedia.org/wiki/Diplacus_aurantiacus",
-#     "tidy tips": "https://en.wikipedia.org/wiki/Layia_platyglossa",
-#     "wild cucumber": "https://en.wikipedia.org/wiki/Marah_(plant)",
-#     "douglas iris": "https://en.wikipedia.org/wiki/Iris_douglasiana",
-#     "goldfields coreopsis": "https://en.wikipedia.org/wiki/Coreopsis"
-# }
-
-# # Templates for AI image generation
-# prompt_templates = [
-#     "A dreamy watercolor scene of a {flower} on a misty morning trail, with golden sunbeams filtering through towering redwoods, and a curious hummingbird hovering nearby.",
-#     "A loose, expressive watercolor sketch of a {flower} in a wild meadow, surrounded by dancing butterflies and morning dew drops sparkling like diamonds in the dawn light.",
-#     "An artist's nature journal page featuring a detailed {flower} study, with delicate ink lines and soft watercolor washes, complete with small sketches of bees and field notes in the margins.",
-#     "A vibrant plein air painting of a {flower} patch along a coastal hiking trail, with crashing waves and rugged cliffs in the background, painted in bold, energetic brushstrokes.",
-#     "A whimsical mixed-media scene of a {flower} garden at sunrise, combining loose watercolor washes with detailed botanical illustrations, featuring hidden wildlife and morning fog rolling through the valley."
-# ]
-
-# # Example images
-# examples = [
-#     str(Path('examples/example_1.jpg')),
-#     str(Path('examples/example_2.jpg')),
-#     str(Path('examples/example_3.jpg')),
-#     str(Path('examples/example_4.jpg')),
-#     str(Path('examples/example_5.jpg'))
-# ]
-
-# # Handle AI generation progress updates
-# def on_queue_update(update):
-#     if isinstance(update, fal_client.InProgress):
-#         for log in update.logs:
-#             print(log["message"])
-
-# # Main processing function
-# def process_image(img):
-#     predicted_class, _, _ = learn.predict(img)
-#     wiki_url = search_terms_wikipedia.get(predicted_class, "No Wikipedia entry found.")
-
-#     result = fal_client.subscribe(
-#         "fal-ai/flux/schnell",
-#         arguments={
-#             "prompt": random.choice(prompt_templates).format(flower=predicted_class),
-#             "image_size": "portrait_4_3"
-#         },
-#         with_logs=True,
-#         on_queue_update=on_queue_update,
-#     )
-
-#     image_url = result['images'][0]['url']
-#     response = requests.get(image_url)
-#     generated_image = Image.open(io.BytesIO(response.content))
-
-#     return predicted_class, generated_image, wiki_url
-
-# # Clear all outputs
-# def clear_outputs():
-#     return {
-#         label_output: None,
-#         generated_image: None,
-#         wiki_output: None
-#     }
-
-# # Load the model
-# learn = load_learner('plants.pkl')
-
-# # Gradio interface
-# with gr.Blocks() as demo:
-#     with gr.Row():
-#         input_image = gr.Image(height=230, width=230, label="Upload Image for Classification", type="pil")
-    
-#     with gr.Row():
-#         with gr.Column():
-#             label_output = gr.Textbox(label="Predicted Plant Name", lines=1)
-#             wiki_output = gr.Textbox(label="Wikipedia Article Link", lines=1)
-#         generated_image = gr.Image(label="AI Generated Interpretation")
-    
-#     gr.Examples(
-#         examples=examples,
-#         inputs=input_image,
-#         examples_per_page=6,
-#         fn=process_image,
-#         outputs=[label_output, generated_image, wiki_output]
-#     )
-    
-#     input_image.change(
-#         fn=process_image,
-#         inputs=input_image,
-#         outputs=[label_output, generated_image, wiki_output]
-#     )
-    
-#     input_image.clear(
-#         fn=clear_outputs,
-#         inputs=[],
-#         outputs=[label_output, generated_image, wiki_output]
-#     )
-
-# # Launch the demo
-# demo.launch(inline=False)
+demo.launch(inline=False)