import os import gradio as gr import re import folium from fastai.vision.all import * from groq import Groq from PIL import Image import time import json from functools import lru_cache # Load the trained model learn = load_learner('export.pkl') labels = learn.dls.vocab # Initialize Groq client client = Groq( api_key=os.environ.get("GROQ_API_KEY"), ) # Cache directory for API responses os.makedirs("cache", exist_ok=True) # Language translations translations = { "en": { "app_title": "AvianEye Tanzania", "app_description": "🔍 Upload a bird photo to instantly identify species and access comprehensive data on habitats, behaviors, and climate change impacts. A powerful tool for Tanzania-based ornithological research.", "upload_label": "Upload Bird Image", "identify_button": "Identify Bird", "predictions_label": "Top 5 Predictions", "bird_info_label": "Bird Information", "research_questions": "Research Questions", "question_placeholder": "Example: How has climate change affected this bird's migration pattern?", "question_label": "Ask a question about this bird", "submit_question": "Submit Question", "clear_conversation": "Clear Conversation", "upload_prompt": "Please upload an image", "question_title": "Question:", "answer_title": "Answer:", "habitat_map_title": "Natural Habitat Map for", "detailed_info_title": "Detailed Information", "language_label": "Language / Lugha", "loading": "Processing...", "low_confidence": "Low confidence prediction. Results may not be accurate.", "not_a_bird": "The image may not contain a bird. Please upload a clear image of a bird.", "other_message": "This image is not in our trained dataset or the image may not be of a bird. Please try uploading a different image.", "examples_title": "Examples" }, "sw": { "app_title": "Mtafiti wa Ndege: Utambuzi wa Kiotomatiki kwa Watafiti", "app_description": "🔍 Pakia picha ya ndege ili kutambua spishi mara moja na kupata data kamili kuhusu makazi, tabia, na athari za mabadiliko ya tabianchi. Zana yenye nguvu kwa utafiti wa ndege nchini Tanzania.", "upload_label": "Pakia Picha ya Ndege", "identify_button": "Tambua Ndege", "predictions_label": "Utabiri Bora 5", "bird_info_label": "Taarifa za Ndege", "research_questions": "Maswali ya Utafiti", "question_placeholder": "Mfano: Je, mabadiliko ya tabianchi yameathiri vipi mfumo wa uhamiaji wa ndege huyu?", "question_label": "Uliza swali kuhusu ndege huyu", "submit_question": "Wasilisha Swali", "clear_conversation": "Futa Mazungumzo", "upload_prompt": "Tafadhali pakia picha", "question_title": "Swali:", "answer_title": "Jibu:", "habitat_map_title": "Ramani ya Makazi Asilia ya", "detailed_info_title": "Taarifa za Kina", "language_label": "Language / Lugha", "loading": "Inachakata...", "low_confidence": "Utabiri wa uhakika mdogo. Matokeo yanaweza kuwa si sahihi.", "not_a_bird": "Picha inaweza isiwe ya ndege. Tafadhali pakia picha wazi ya ndege.", "other_message": "Ndege huyu haipatikani katika hifadhidata yetu au picha inaweza isiwe ya ndege. Tafadhali jaribu kupakia picha nyingine.", "examples_title": "Mifano" } } # Example images configuration EXAMPLE_IMAGES = [ {"path": "image.jpg", "name": "Example image"}, {"path": "image1.webp", "name": "Example image2"}, {"path": "image2.jpg", "name": "Example image3"}, {"path": "image3.jpg", "name": "Example image4"} ] def clean_bird_name(name): """Clean bird name by removing numbers and special characters, and fix formatting""" # Remove numbers and dots at the beginning cleaned = re.sub(r'^\d+\.', '', name) # Replace underscores with spaces cleaned = cleaned.replace('_', ' ') # Remove any remaining special characters cleaned = re.sub(r'[^\w\s]', '', cleaned) # Fix spacing cleaned = ' '.join(cleaned.split()) return cleaned def get_cache_path(function_name, key): """Generate a cache file path""" safe_key = re.sub(r'[^\w]', '_', key) return f"cache/{function_name}_{safe_key}.json" def save_to_cache(function_name, key, data): """Save API response to cache""" try: cache_path = get_cache_path(function_name, key) with open(cache_path, 'w') as f: json.dump({"data": data, "timestamp": time.time()}, f) except Exception as e: print(f"Error saving to cache: {e}") def load_from_cache(function_name, key, max_age=86400): # Default max age: 1 day """Load API response from cache if it exists and is not too old""" try: cache_path = get_cache_path(function_name, key) if os.path.exists(cache_path): with open(cache_path, 'r') as f: cached = json.load(f) if time.time() - cached["timestamp"] < max_age: return cached["data"] except Exception as e: print(f"Error loading from cache: {e}") return None def is_likely_bird_image(img): """Basic check to see if the image might contain a bird""" try: # Convert to numpy array for analysis img_array = np.array(img) # Simple checks that might indicate a bird isn't present: # 1. Check if image is too dark or too bright overall mean_brightness = np.mean(img_array) if mean_brightness < 20 or mean_brightness > 235: return False # 2. Check if image has very little color variation (might be a solid background) std_dev = np.std(img_array) if std_dev < 15: return False # 3. If image is very small, it might not be a useful bird photo if img_array.shape[0] < 100 or img_array.shape[1] < 100: return False return True except: # If any error occurs during the check, assume it might be a bird return True def get_bird_habitat_and_status(bird_name): """Get both habitat locations and Tanzania status in a single API call""" clean_name = clean_bird_name(bird_name) # Check cache first - use a combined cache key cache_key = f"{clean_name}_combined" cached_result = load_from_cache("combined_habitat_status", cache_key) if cached_result is not None: return cached_result["locations"], cached_result["is_in_tanzania"] # Single API call to get both information prompt = f""" Provide information about the {clean_name} bird in the following JSON format: {{ "is_native_to_tanzania": true/false, "habitat_locations": [ {{ "name": "Location name", "lat": latitude_number, "lon": longitude_number, "description": "Brief description of habitat" }} ] }} Instructions: 1. Set "is_native_to_tanzania" to true if this bird is native to, endemic to, or commonly found in Tanzania. Set to false if it's not typically found there. 2. Provide 3-5 main habitat locations worldwide for this bird species. 3. If the bird IS native to Tanzania, include Tanzania or East African locations in the habitat list. 4. If the bird is NOT native to Tanzania, do not include any Tanzania locations. 5. Return ONLY the JSON response, no additional text. """ try: chat_completion = client.chat.completions.create( messages=[ { "role": "user", "content": prompt, } ], model="llama-3.3-70b-versatile", ) response = chat_completion.choices[0].message.content # Extract and parse JSON from response import json import re # Find JSON pattern in response json_match = re.search(r'\{.*\}', response, re.DOTALL) if json_match: result = json.loads(json_match.group()) locations = result.get("habitat_locations", []) is_in_tanzania = result.get("is_native_to_tanzania", False) else: # Fallback if JSON parsing fails locations = [ {"name": "Primary habitat region", "lat": 0, "lon": 0, "description": "Could not retrieve specific habitat information for this bird."} ] is_in_tanzania = False # Ensure we have valid data structure if not locations: locations = [ {"name": "Unknown habitat", "lat": 0, "lon": 0, "description": "Habitat information not available."} ] # Cache the combined result combined_result = { "locations": locations, "is_in_tanzania": is_in_tanzania } save_to_cache("combined_habitat_status", cache_key, combined_result) return locations, is_in_tanzania except Exception as e: print(f"Error in get_bird_habitat_and_status: {e}") return [{"name": "Error retrieving data", "lat": 0, "lon": 0, "description": "Please try again or check your connection."}], False def create_habitat_map(habitat_locations): """Create a folium map with the habitat locations""" # Find center point based on valid coordinates valid_coords = [(loc.get("lat", 0), loc.get("lon", 0)) for loc in habitat_locations if loc.get("lat", 0) != 0 or loc.get("lon", 0) != 0] if valid_coords: # Calculate the average of the coordinates avg_lat = sum(lat for lat, _ in valid_coords) / len(valid_coords) avg_lon = sum(lon for _, lon in valid_coords) / len(valid_coords) # Create map centered on the average coordinates m = folium.Map(location=[avg_lat, avg_lon], zoom_start=3) else: # Default world map if no valid coordinates m = folium.Map(location=[20, 0], zoom_start=2) # Add markers for each habitat location for location in habitat_locations: name = location.get("name", "Unknown") lat = location.get("lat", 0) lon = location.get("lon", 0) description = location.get("description", "No description available") # Skip invalid coordinates if lat == 0 and lon == 0: continue # Add marker folium.Marker( location=[lat, lon], popup=folium.Popup(f"{name}
{description}", max_width=300), tooltip=name ).add_to(m) # Save map to HTML map_html = m._repr_html_() return map_html def format_bird_info(raw_info, is_in_tanzania, language="en"): """Improve the formatting of bird information""" # Add proper line breaks between sections and ensure consistent heading levels formatted = raw_info # Only add the warning if the bird is NOT in Tanzania if not is_in_tanzania: # Get translation of warning text based on language warning_text = "NOT TYPICALLY FOUND IN TANZANIA" warning_translation = "HAPATIKANI SANA TANZANIA" if language == "sw" else warning_text # Add warning at the beginning if not already present if warning_translation not in formatted: formatted = f'
⚠️ {warning_translation}
\n\n{formatted}' # Replace markdown headings with HTML headings for better control formatted = re.sub(r'#+\s+(.*)', r'

\1

', formatted) # Add paragraph tags for better spacing formatted = re.sub(r'\n\*\s+(.*)', r'

• \1

', formatted) formatted = re.sub(r'\n([^<\n].*)', r'

\1

', formatted) # Remove any duplicate paragraph tags formatted = formatted.replace('

', '

') formatted = formatted.replace('

', '

') return formatted def get_bird_info(bird_name, is_in_tanzania, language="en"): """Get detailed information about a bird using Groq API with caching""" clean_name = clean_bird_name(bird_name) # Check cache first - include Tanzania status in cache key cache_key = f"{clean_name}_{language}_{is_in_tanzania}" cached_info = load_from_cache("bird_info", cache_key) if cached_info is not None: return cached_info # Adjust language for the prompt lang_instruction = "" if language == "sw": lang_instruction = " Provide your response in Swahili language." # Adjust prompt based on Tanzania status tanzania_instruction = "" if not is_in_tanzania: tanzania_instruction = " Important: This bird is NOT typically found in Tanzania. Explain why its presence might be unusual and focus on its natural range." else: tanzania_instruction = " This bird is native to or commonly found in Tanzania. Include information about its presence in Tanzania and East Africa." prompt = f""" Provide detailed information about the {clean_name} bird, including: 1. Physical characteristics and appearance 2. Habitat and distribution 3. Diet and behavior 4. Migration patterns (emphasize if this pattern has changed in recent years due to climate change) 5. Conservation status {tanzania_instruction} Format your response in markdown for better readability.{lang_instruction} """ try: chat_completion = client.chat.completions.create( messages=[ { "role": "user", "content": prompt, } ], model="llama-3.3-70b-versatile", ) response = chat_completion.choices[0].message.content # Cache the result save_to_cache("bird_info", cache_key, response) return response except Exception as e: error_msg = "Hitilafu katika kupata taarifa" if language == "sw" else "Error fetching information" return f"{error_msg}: {str(e)}" def create_message_html(message, icon="🔍", language="en"): """Create a styled message container for notifications""" custom_css = """ """ html = f""" {custom_css}
{icon}
{message}
""" return html def load_example_image(image_path): """Load example image for testing""" try: if os.path.exists(image_path): return Image.open(image_path) else: print(f"Example image not found: {image_path}") return None except Exception as e: print(f"Error loading example image: {e}") return None def predict_and_get_info(img, language="en"): """Predict bird species and get detailed information""" # Get translations t = translations[language] # Check if an image was provided if img is None: message = t['upload_prompt'] return None, create_message_html(message, "📷", language), "", "" # Basic check if the image might contain a bird if not is_likely_bird_image(img): message = t['not_a_bird'] return None, create_message_html(message, "⚠️", language), "", "" try: # Process the image img = PILImage.create(img) # Get prediction pred, pred_idx, probs = learn.predict(img) # Get top 5 predictions (or all if less than 5) num_classes = min(5, len(labels)) top_indices = probs.argsort(descending=True)[:num_classes] top_probs = probs[top_indices] top_labels = [labels[i] for i in top_indices] # Format as dictionary with cleaned names for display prediction_results = {clean_bird_name(top_labels[i]): float(top_probs[i]) for i in range(num_classes)} # Get top prediction (original format for info retrieval) top_bird = str(pred) # Also keep a clean version for display clean_top_bird = clean_bird_name(top_bird) # Check if the model's confidence is low if float(top_probs[0]) < 0.4: low_confidence_warning = t['low_confidence'] else: low_confidence_warning = "" # Check if the top prediction is "Other" and has high confidence if "other" in clean_top_bird.lower(): # Create a message informing the user that the bird wasn't recognized other_message = t['other_message'] combined_info = create_message_html(other_message, "🔍", language) return prediction_results, combined_info, clean_top_bird, "" # Get habitat locations and Tanzania status in a single call habitat_locations, is_in_tanzania = get_bird_habitat_and_status(top_bird) habitat_map_html = create_habitat_map(habitat_locations) # Get detailed information about the top predicted bird bird_info = get_bird_info(top_bird, is_in_tanzania, language) formatted_info = format_bird_info(bird_info, is_in_tanzania, language) # Create combined info with map at the top and properly formatted information custom_css = """ """ # Add low confidence warning if needed confidence_warning_html = f'
{low_confidence_warning}
' if low_confidence_warning else '' combined_info = f""" {custom_css}
{confidence_warning_html}

{t['habitat_map_title']} {clean_top_bird}

{habitat_map_html}

{t['detailed_info_title']}

{formatted_info}
""" return prediction_results, combined_info, clean_top_bird, "" except Exception as e: error_msg = "Hitilafu katika kuchakata picha" if language == "sw" else "Error processing image" return None, create_message_html(f"{error_msg}: {str(e)}", "⚠️", language), "", "" def follow_up_question(question, bird_name, language="en"): """Allow researchers to ask follow-up questions about the identified bird""" t = translations[language] if not question.strip() or not bird_name: return "Please identify a bird first and ask a specific question about it." if language == "en" else "Tafadhali tambua ndege kwanza na uulize swali maalum kuhusu ndege huyo." # Check cache first cache_key = f"{bird_name}_{question}_{language}".replace(" ", "_")[:100] # Limit key length cached_answer = load_from_cache("follow_up", cache_key) if cached_answer is not None: return cached_answer # Adjust language for the prompt lang_instruction = "" if language == "sw": lang_instruction = " Provide your response in Swahili language." prompt = f""" The researcher is asking about the {bird_name} bird: "{question}" Provide a detailed, scientific answer focusing on accurate ornithological information. If the question relates to Tanzania or climate change impacts, emphasize those aspects in your response. IMPORTANT: Do not repeat basic introductory information about the bird that would have already been provided in a general description. Do not start your answer with phrases like "Introduction to the {bird_name}" or similar repetitive headers. Directly answer the specific question asked. Format your response in markdown for better readability.{lang_instruction} """ try: chat_completion = client.chat.completions.create( messages=[ { "role": "user", "content": prompt, } ], model="llama-3.3-70b-versatile", ) response = chat_completion.choices[0].message.content # Cache the result save_to_cache("follow_up", cache_key, response) return response except Exception as e: error_msg = "Hitilafu katika kupata taarifa" if language == "sw" else "Error fetching information" return f"{error_msg}: {str(e)}" def get_available_examples(): """Get list of available example images that actually exist""" available_examples = [] for example in EXAMPLE_IMAGES: if os.path.exists(example["path"]): available_examples.append(example) return available_examples # Create the Gradio interface with gr.Blocks(theme=gr.themes.Soft()) as app: # Current language and bird state current_lang = gr.State("en") current_bird = gr.State("") # Header with language switcher with gr.Row(): with gr.Column(scale=3): title_md = gr.Markdown(f"# {translations['en']['app_title']}") with gr.Column(scale=1): language_selector = gr.Radio( choices=["English", "Kiswahili"], label=translations['en']['language_label'], value="English" ) # App description description_md = gr.Markdown(f"{translations['en']['app_description']}") # Main identification section with gr.Row(): with gr.Column(scale=1): input_image = gr.Image(type="pil", label=translations['en']['upload_label']) submit_btn = gr.Button(translations['en']['identify_button'], variant="primary") with gr.Column(scale=2): prediction_output = gr.Label(label=translations['en']['predictions_label'], num_top_classes=5) bird_info_output = gr.HTML(label=translations['en']['bird_info_label']) # Examples section - horizontal layout below main content examples_header = gr.Markdown(f"### {translations['en']['examples_title']}") # Create horizontal row of example images available_examples = get_available_examples() if available_examples: with gr.Row(): example_buttons = [] for example in available_examples: with gr.Column(scale=1): example_image = gr.Image( value=example["path"], label=example["name"], show_label=True, interactive=False, height=150 ) example_btn = gr.Button( f"Use {example['name']}", size="sm", variant="secondary" ) example_buttons.append((example_btn, example["path"])) else: gr.Markdown("*No example images available*") # Clear divider gr.Markdown("---") # Follow-up question section with improved UI questions_header = gr.Markdown(f"## {translations['en']['research_questions']}") conversation_history = gr.Markdown("") with gr.Row(): follow_up_input = gr.Textbox( label=translations['en']['question_label'], placeholder=translations['en']['question_placeholder'], lines=2 ) with gr.Row(): follow_up_btn = gr.Button(translations['en']['submit_question'], variant="primary") clear_btn = gr.Button(translations['en']['clear_conversation']) # Functions for event handlers def update_conversation(question, bird_name, history, lang): t = translations[lang] if not question.strip(): return history answer = follow_up_question(question, bird_name, lang) # Format the conversation with clear separation new_exchange = f""" ### {t['question_title']} {question} ### {t['answer_title']} {answer} --- """ updated_history = new_exchange + history return updated_history def clear_conversation_history(): return "" def update_language(choice): # Convert selection to language code lang = "sw" if choice == "Kiswahili" else "en" t = translations[lang] # Return updated UI components based on selected language return ( lang, f"# {t['app_title']}", f"{t['app_description']}", t['upload_label'], t['identify_button'], t['predictions_label'], t['bird_info_label'], f"### {t['examples_title']}", f"## {t['research_questions']}", t['question_label'], t['question_placeholder'], t['submit_question'], t['clear_conversation'] ) def use_example_image(image_path): """Load and return example image""" return load_example_image(image_path) # Set up event handlers language_selector.change( update_language, inputs=[language_selector], outputs=[ current_lang, title_md, description_md, input_image, submit_btn, prediction_output, bird_info_output, examples_header, questions_header, follow_up_input, follow_up_input, follow_up_btn, clear_btn ] ) # Set up example button event handlers if available_examples: for example_btn, image_path in example_buttons: example_btn.click( use_example_image, inputs=[gr.State(image_path)], outputs=[input_image] ) # Add loading state for better UX submit_btn.click( lambda x, y: (None, create_message_html(translations[y]['loading'], "⏳", y), "", ""), inputs=[input_image, current_lang], outputs=[prediction_output, bird_info_output, current_bird, conversation_history] ).then( predict_and_get_info, inputs=[input_image, current_lang], outputs=[prediction_output, bird_info_output, current_bird, conversation_history] ) follow_up_btn.click( update_conversation, inputs=[follow_up_input, current_bird, conversation_history, current_lang], outputs=[conversation_history] ).then( lambda: "", outputs=follow_up_input ) clear_btn.click( clear_conversation_history, outputs=[conversation_history] ) # Launch the app app.launch(share=True)