Update app.py

app.py

@@ -7,51 +7,70 @@ import random
 import requests
 from pathlib import Path
 
-# Load your model
+# Load model
 learn = load_learner('resnet50_30_categories.pkl')
 
-# Wikipedia links
+# Wikipedia links dictionary
 search_terms_wikipedia = {
     "blazing star": "https://en.wikipedia.org/wiki/Mentzelia",
     "bristlecone pine": "https://en.wikipedia.org/wiki/Pinus_longaeva",
-    # ... (same as before)
+    "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"
 }
 
-# Prompt templates for art generation
+# Prompt templates for AI 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."
+    "A dreamy watercolor scene of a {flower} on a misty morning trail...",
+    "A loose, expressive watercolor sketch of a {flower} in a wild meadow...",
+    "An artist's nature journal page featuring a detailed {flower} study...",
+    "A vibrant plein air painting of a {flower} patch along a coastal trail...",
+    "A whimsical mixed-media scene of a {flower} garden at sunrise..."
 ]
 
-# Example image paths (replace with actual paths on your system or Hugging Face space)
+# Local example image paths
 example_images = [
-    str(Path('example_images/example_1.jpg')),
-    str(Path('example_images/example_2.jpg')),
-    str(Path('example_images/example_3.jpg')),
-    str(Path('example_images/example_4.jpg')),
-    str(Path('example_images/example_5.jpg'))
+    str(Path("example_images/example_1.jpg")),
+    str(Path("example_images/example_2.jpg")),
+    str(Path("example_images/example_3.jpg")),
+    str(Path("example_images/example_4.jpg")),
+    str(Path("example_images/example_5.jpg")),
 ]
 
+# Logging for FAL client
 def on_queue_update(update):
     if isinstance(update, fal_client.InProgress):
         for log in update.logs:
             print(log["message"])
-    else:
-        print("Received non-InProgress update:", update)
 
-# Processing function
+# Process image and return classification + AI-generated artwork + Wiki URL
 def process_image(img):
     predicted_class, _, probs = learn.predict(img)
     classification_results = dict(zip(learn.dls.vocab, map(float, probs)))
-
-    # Wikipedia
     wiki_url = search_terms_wikipedia.get(predicted_class.lower(), "No Wikipedia entry found.")
 
-    # Generate image via FAL
+    # Generate image via FAL API
     result = fal_client.subscribe(
         "fal-ai/flux/schnell",
         arguments={
@@ -62,35 +81,34 @@ def process_image(img):
         on_queue_update=on_queue_update,
     )
 
-    image_url = result['images'][0]['url']
+    image_url = result["images"][0]["url"]
     response = requests.get(image_url)
     generated_image = Image.open(io.BytesIO(response.content))
 
-    return classification_results, generated_image, wiki_url
+    return classification_results, generated_image, str(wiki_url)
 
-# Interface
+# Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("# 🌼 Wildflower Classifier & Artistic Generator")
+    gr.Markdown("# 🌼 California Native Plant Classifier & AI Art Generator")
 
     with gr.Row():
-        input_image = gr.Image(height=230, width=230, label="Upload an image", type="pil")
+        input_image = gr.Image(type="pil", label="Upload a Photo", height=250)
 
     with gr.Row():
         with gr.Column():
-            label_output = gr.Label(label="Prediction")
+            label_output = gr.Label(label="Classification Results")
             wiki_output = gr.Textbox(label="Wikipedia Link")
-        generated_image = gr.Image(label="AI Artistic Interpretation")
+        generated_image = gr.Image(label="AI-Generated Artistic Interpretation")
+
+    # Submit button to trigger image processing
+    submit_btn = gr.Button("Submit")
+    submit_btn.click(fn=process_image, inputs=input_image, outputs=[label_output, generated_image, wiki_output])
 
+    # Examples
     gr.Examples(
         examples=example_images,
         inputs=input_image,
         examples_per_page=6
     )
 
-    input_image.upload(
-        fn=process_image,
-        inputs=input_image,
-        outputs=[label_output, generated_image, wiki_output]
-    )
-
 demo.launch()