| from fastai.vision.all import *
|
| import gradio as gr
|
| import fal_client
|
| from PIL import Image
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| import io
|
| import random
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| import requests
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| from pathlib import Path
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|
|
|
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|
|
|
|
| search_terms_wikipedia = {
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| "blazing star": "https://en.wikipedia.org/wiki/Mentzelia",
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| "bristlecone pine": "https://en.wikipedia.org/wiki/Pinus_longaeva",
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| "california bluebell": "https://en.wikipedia.org/wiki/Phacelia_minor",
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| "california buckeye": "https://en.wikipedia.org/wiki/Aesculus_californica",
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| "california buckwheat": "https://en.wikipedia.org/wiki/Eriogonum_fasciculatum",
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| "california fuchsia": "https://en.wikipedia.org/wiki/Epilobium_canum",
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| "california checkerbloom": "https://en.wikipedia.org/wiki/Sidalcea_malviflora",
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| "california lilac": "https://en.wikipedia.org/wiki/Ceanothus",
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| "california poppy": "https://en.wikipedia.org/wiki/Eschscholzia_californica",
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| "california sagebrush": "https://en.wikipedia.org/wiki/Artemisia_californica",
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| "california wild grape": "https://en.wikipedia.org/wiki/Vitis_californica",
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| "california wild rose": "https://en.wikipedia.org/wiki/Rosa_californica",
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| "coyote mint": "https://en.wikipedia.org/wiki/Monardella",
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| "elegant clarkia": "https://en.wikipedia.org/wiki/Clarkia_unguiculata",
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| "baby blue eyes": "https://en.wikipedia.org/wiki/Nemophila_menziesii",
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| "hummingbird sage": "https://en.wikipedia.org/wiki/Salvia_spathacea",
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| "delphinium": "https://en.wikipedia.org/wiki/Delphinium",
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| "matilija poppy": "https://en.wikipedia.org/wiki/Romneya_coulteri",
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| "blue-eyed grass": "https://en.wikipedia.org/wiki/Sisyrinchium_bellum",
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| "penstemon spectabilis": "https://en.wikipedia.org/wiki/Penstemon_spectabilis",
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| "seaside daisy": "https://en.wikipedia.org/wiki/Erigeron_glaucus",
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| "sticky monkeyflower": "https://en.wikipedia.org/wiki/Diplacus_aurantiacus",
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| "tidy tips": "https://en.wikipedia.org/wiki/Layia_platyglossa",
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| "wild cucumber": "https://en.wikipedia.org/wiki/Marah_(plant)",
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| "douglas iris": "https://en.wikipedia.org/wiki/Iris_douglasiana",
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| "goldfields coreopsis": "https://en.wikipedia.org/wiki/Coreopsis"
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| }
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|
|
|
|
|
|
|
|
| prompt_templates = [
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|
|
| "A dreamy watercolor painting of a {flower} in a magical forest with glowing sunlight and butterflies.",
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|
|
| "A cinematic artistic interpretation of a {flower} blooming beside a mountain trail at sunrise.",
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|
|
| "A fantasy botanical artwork featuring a {flower} surrounded by mist and colorful wildlife.",
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|
|
| "An impressionist oil painting of a {flower} field with vibrant brush strokes and golden light.",
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|
|
| "A detailed nature journal illustration of a {flower} with artistic sketches and handwritten notes."
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| ]
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|
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|
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|
|
|
|
| example_images = [
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| str(Path("example_images/example_1.jpg")),
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| str(Path("example_images/example_2.jpg")),
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| str(Path("example_images/example_3.jpg")),
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| str(Path("example_images/example_4.jpg")),
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| str(Path("example_images/example_5.jpg"))
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| ]
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|
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|
|
|
|
|
| learn = load_learner("resnet50_30_categories.pkl")
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|
|
|
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|
|
|
|
| def on_queue_update(update):
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|
|
| if isinstance(update, fal_client.InProgress):
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|
|
| for log in update.logs:
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|
|
| print(log["message"])
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|
|
|
|
|
|
|
|
| def process_image(
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| img,
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| art_style,
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| creativity_level,
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| image_quality
|
| ):
|
|
|
| if img is None:
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|
|
| return (
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| None,
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| None,
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| "⚠️ Please upload a flower image.",
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| {}
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| )
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|
|
|
|
|
|
|
|
| predicted_class, _, probs = learn.predict(img)
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|
|
| classification_results = dict(
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| zip(
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| learn.dls.vocab,
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| map(float, probs)
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| )
|
| )
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|
|
| confidence = max(classification_results.values()) * 100
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|
|
|
|
|
|
|
|
| wiki_url = search_terms_wikipedia.get(
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| predicted_class,
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| "No article found."
|
| )
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|
|
|
|
|
|
|
|
| prompt = random.choice(
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| prompt_templates
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| ).format(
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| flower=predicted_class
|
| )
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|
|
| final_prompt = f"""
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| {prompt}
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|
|
| Style: {art_style}
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|
|
| Creativity Level: {creativity_level}
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|
|
| Image Quality: {image_quality}
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| """
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|
|
|
|
|
|
|
|
| result = fal_client.subscribe(
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| "fal-ai/flux/schnell",
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| arguments={
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| "prompt": final_prompt,
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| "image_size": "portrait_4_3"
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| },
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| with_logs=True,
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| on_queue_update=on_queue_update,
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| )
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|
|
| image_url = result["images"][0]["url"]
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|
|
| response = requests.get(image_url)
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|
|
| generated_image = Image.open(
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| io.BytesIO(response.content)
|
| )
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|
|
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|
|
|
|
|
| result_text = f"""
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| # 🌸 Flower Classification Complete
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|
|
| ### Predicted Flower:
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| ## {predicted_class.title()}
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|
|
| ### Confidence Score:
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| ## {confidence:.2f}%
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|
|
| ### AI artistic interpretation generated successfully.
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| """
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|
|
|
|
|
|
|
|
| sorted_results = dict(
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| sorted(
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| classification_results.items(),
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| key=lambda x: x[1],
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| reverse=True
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| )[:5]
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| )
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|
|
| return (
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| generated_image,
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| wiki_url,
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| result_text,
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| sorted_results
|
| )
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|
|
|
|
|
|
|
|
| custom_css = """
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| body {
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| background: #f5f7fb;
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| font-family: 'Segoe UI', sans-serif;
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| }
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|
|
| .gradio-container {
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| max-width: 1350px !important;
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| margin: auto;
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| }
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|
|
| .hero {
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| background: linear-gradient(135deg,#065f46,#16a34a);
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| padding: 40px;
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| border-radius: 30px;
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| color: white;
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| margin-bottom: 20px;
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| }
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|
|
| .hero h1 {
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| font-size: 52px;
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| font-weight: 800;
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| margin-bottom: 10px;
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| }
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|
|
| .hero p {
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| font-size: 18px;
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| opacity: 0.92;
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| }
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|
|
| .card {
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| background: white;
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| border-radius: 24px;
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| padding: 22px;
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| box-shadow: 0 6px 18px rgba(0,0,0,0.08);
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| }
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|
|
| button {
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| height: 60px !important;
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| border-radius: 18px !important;
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| border: none !important;
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| background: linear-gradient(135deg,#16a34a,#15803d) !important;
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| color: white !important;
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| font-size: 20px !important;
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| font-weight: 700 !important;
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| }
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|
|
| button:hover {
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| background: linear-gradient(135deg,#15803d,#166534) !important;
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| }
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|
|
| input, textarea, select {
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| border-radius: 16px !important;
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| }
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|
|
| @media (max-width:768px){
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|
|
| .hero {
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| padding: 22px;
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| }
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|
|
| .hero h1 {
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| font-size: 32px;
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| }
|
|
|
| .hero p {
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| font-size: 15px;
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| }
|
|
|
| button {
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| height: 54px !important;
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| font-size: 17px !important;
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| }
|
| }
|
| """
|
|
|
|
|
|
|
|
|
| hero_html = """
|
| <div class="hero">
|
|
|
| <h1>🌸 AI Flower Classifier & Art Generator</h1>
|
|
|
| <p>
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| Upload flower images, identify plant species instantly, and generate AI-powered artistic interpretations.
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| Modern responsive interface optimized for mobile and desktop devices.
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| </p>
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|
|
| </div>
|
| """
|
|
|
|
|
|
|
|
|
| with gr.Blocks(
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| css=custom_css,
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| theme=gr.themes.Soft(
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| primary_hue="green",
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| secondary_hue="emerald"
|
| )
|
| ) as demo:
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|
|
| gr.HTML(hero_html)
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|
|
|
|
|
|
|
|
| with gr.Row():
|
|
|
| with gr.Column():
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| gr.Markdown("""
|
| ### ⚡ Fast AI Recognition
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| Instant flower classification
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| """)
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|
|
| with gr.Column():
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| gr.Markdown("""
|
| ### 🎨 AI Art Generator
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| Create artistic flower scenes
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| """)
|
|
|
| with gr.Column():
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| gr.Markdown("""
|
| ### 📱 Mobile Responsive
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| Optimized modern UI
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| """)
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|
|
|
|
|
|
|
|
| with gr.Row():
|
|
|
|
|
|
|
|
|
| with gr.Column(scale=1):
|
|
|
| input_image = gr.Image(
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| type="pil",
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| label="🌸 Upload Flower Image"
|
| )
|
|
|
| art_style = gr.Dropdown(
|
| choices=[
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| "Watercolor",
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| "Oil Painting",
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| "Fantasy Art",
|
| "Impressionist",
|
| "Botanical Illustration"
|
| ],
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| value="Watercolor",
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| label="🎨 Art Style"
|
| )
|
|
|
| creativity_level = gr.Slider(
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| minimum=10,
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| maximum=100,
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| value=75,
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| step=5,
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| label="🧠 Creativity Level"
|
| )
|
|
|
| image_quality = gr.Dropdown(
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| choices=[
|
| "Standard",
|
| "High",
|
| "Ultra"
|
| ],
|
| value="High",
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| label="✨ Image Quality"
|
| )
|
|
|
| generate_btn = gr.Button(
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| "🚀 Analyze & Generate Art",
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| variant="primary"
|
| )
|
|
|
|
|
|
|
|
|
| with gr.Column(scale=1):
|
|
|
| output_image = gr.Image(
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| label="🖌️ AI Artistic Interpretation"
|
| )
|
|
|
| wiki_output = gr.Textbox(
|
| label="📚 Wikipedia Article",
|
| lines=1
|
| )
|
|
|
| result_output = gr.Markdown()
|
|
|
| probability_output = gr.Label(
|
| label="📊 Top Predictions"
|
| )
|
|
|
|
|
|
|
|
|
| gr.Examples(
|
| examples=example_images,
|
| inputs=input_image
|
| )
|
|
|
|
|
|
|
|
|
| generate_btn.click(
|
| fn=process_image,
|
| inputs=[
|
| input_image,
|
| art_style,
|
| creativity_level,
|
| image_quality
|
| ],
|
| outputs=[
|
| output_image,
|
| wiki_output,
|
| result_output,
|
| probability_output
|
| ]
|
| )
|
|
|
|
|
|
|
|
|
| demo.launch() |
