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app.py

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+import streamlit as st
+import cv2
+import requests
+import tempfile
+from ultralytics import YOLO
+from PIL import Image
+import numpy as np
+import os
+
+# Hugging Face API Key
+HF_API_KEY = os.getenv("HF_API_KEY")
+API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.2"
+headers = {"Authorization": f"Bearer {HF_API_KEY}"}
+
+final_birds = None
+
+# Load YOLO Model
+model = YOLO('best_v11-60epochs.pt')
+bird_name = None
+# Styling
+st.markdown(
+    """
+    <style>
+        .stApp {
+            color: var(--text-color);
+        }
+        
+        .title {
+            font-size: 36px;
+            font-weight: bold;
+            text-align: center;
+            color: #4B9FE1;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            gap: 10px;
+            margin-bottom: 5px;
+        }
+        
+        .subtext {
+            font-size: 16px;
+            text-align: center;
+            opacity: 0.8;
+            margin-bottom: 10px;
+        }
+        
+        .bird-count {
+            font-size: 22px;
+            font-weight: bold;
+            color: #FF7F50;
+            text-align: center;
+            margin: 20px 0;
+        }
+        
+        .info-box {
+            background-color: rgba(255, 255, 255, 0.05);
+            padding: 20px;
+            border-radius: 10px;
+            border: 1px solid rgba(255, 255, 255, 0.1);
+            margin: 15px 0;
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        }
+        
+        .bird-info {
+            margin: 8px 0;
+            padding: 8px;
+            background-color: rgba(255, 255, 255, 0.05);
+            border-radius: 5px;
+            color: inherit;
+        }
+        
+        .info-label {
+            font-weight: bold;
+            color: #4B9FE1;
+            margin-right: 10px;
+        }
+        
+        .bird-name {
+            color: #4B9FE1;
+            font-size: 1.5em;
+            margin-bottom: 15px;
+        }
+    </style>
+    """,
+    unsafe_allow_html=True
+)
+
+# App Header
+st.markdown('<p class="title">🦜 Birdscribe AI</p><p class="subtext">Detect birds in images and videos using AI-powered vision.</p>', unsafe_allow_html=True)
+
+def extract_clean_info(text):
+    """Extract and clean bird information from LLM response."""
+    # Define the expected fields
+    fields = [
+        "Scientific Name",
+        "Common Names",
+        "Geographical Distribution",
+        "Size",
+        "Weight",
+        "Feet Type",
+        "Lifespan"
+    ]
+    
+    # Initialize dictionary to store the information
+    info_dict = {}
+    
+    # Process each line
+    lines = text.split('\n')
+    
+    for line in lines:
+        line = line.strip()
+        # Skip empty lines
+        if not line:
+            continue
+        
+        # Check if this line contains field information
+        for field in fields:
+            if field.lower() in line.lower() and ":" in line:
+                parts = line.split(':', 1)
+                if len(parts) > 1:
+                    info_dict[field] = parts[1].strip()
+                    break
+            # Handle numbered format: "1. Scientific Name: Icterus parisorum"
+            elif line.startswith(f"{fields.index(field) + 1}.") and field.lower() in line.lower() and ":" in line:
+                parts = line.split(':', 1)
+                if len(parts) > 1:
+                    info_dict[field] = parts[1].strip()
+                    break
+    
+    # Return formatted string with collected information
+    result = []
+    for field in fields:
+        if field in info_dict and info_dict[field]:
+            result.append(f"{field}: {info_dict[field]}")
+            
+    return '\n'.join(result)
+
+def query_bird_info(bird_name):
+    """Query bird information from Mistral API with clear formatting instructions."""
+    prompt = f"""Provide detailed information about the bird species '{bird_name}' using the exact format below:
+
+Scientific Name: [scientific name]
+Common Names: [common names]
+Geographical Distribution: [distribution info]
+Size: [size measurements]
+Weight: [weight range]
+Feet Type: [feet description]
+Lifespan: [lifespan info]
+
+Important: Include the labels exactly as shown above, followed by a colon and the information.
+"""
+    
+    try:
+        response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
+        if response.status_code != 200:
+            st.error(f"API Error: {response.status_code}")
+            return None
+            
+        result = response.json()[0]["generated_text"]
+        return extract_clean_info(result)
+    except Exception as e:
+        st.error(f"Error querying bird information: {str(e)}")
+        return None
+
+def format_bird_info(info_text):
+    """Format bird information for HTML display."""
+    if not info_text:
+        return "<div class='bird-info'>Information not available</div>"
+        
+    formatted_html = ""
+    for line in info_text.split('\n'):
+        if ':' in line:
+            parts = line.split(':', 1)
+            if len(parts) == 2:
+                label, value = parts
+                formatted_html += f"<div class='bird-info'><span class='info-label'>{label.strip()}</span>{value.strip()}</div>"
+    
+    return formatted_html
+
+# File upload section
+upload_type = st.selectbox(
+    "Choose file type",
+    ["Image", "Video"],
+    key="file_type"
+)
+
+# Set allowed file types
+if upload_type == "Image":
+    allowed_types = ["jpg", "jpeg", "png"]
+    upload_message = "Upload an image (JPG, JPEG, PNG)"
+else:
+    allowed_types = ["mp4", "avi", "mpeg4"]
+    upload_message = "Upload a video (MP4, AVI, MPEG4)"
+
+uploaded_file = st.file_uploader(upload_message, type=allowed_types)
+
+if uploaded_file is not None:
+    bird_info = {}
+
+    if upload_type == "Image":
+        # Process image
+        image = Image.open(uploaded_file)
+        if image.mode == 'RGBA':
+            image = image.convert('RGB')
+        
+        st.image(image, caption="Uploaded Image", use_container_width=True)
+
+        # Convert PIL to Numpy array for YOLO
+        image_np = np.array(image)
+        if len(image_np.shape) == 2:
+            image_np = cv2.cvtColor(image_np, cv2.COLOR_GRAY2RGB)
+        elif image_np.shape[-1] == 4:
+            image_np = cv2.cvtColor(image_np, cv2.COLOR_RGBA2RGB)
+
+        # Run detection
+        results = model(image_np)
+        annotated_frame = results[0].plot()
+
+        # Get detected bird names
+        detected_names = []
+        if results[0].boxes:
+            for box in results[0].boxes:
+                class_id = int(box.cls)
+                if class_id in model.names:
+                    detected_names.append(model.names[class_id])
+        
+        if not detected_names:
+            detected_names = ["No birds detected"]
+
+        # Display annotated image
+        st.image(annotated_frame, caption="Detected Objects", use_container_width=True)
+
+        # Display detected birds count
+        st.markdown(f'<p class="bird-count">Detected Bird(s): {", ".join(detected_names)}</p>', unsafe_allow_html=True)
+
+        # Get and display bird information
+        if "No birds detected" not in detected_names:
+            with st.spinner("Retrieving bird information..."):
+                for bird_name in detected_names:
+                    if bird_name not in bird_info:
+                        info = query_bird_info(bird_name)
+                        if info:
+                            st.markdown(
+                                f'<div class="info-box">'
+                                f'<h3 class="bird-name">{bird_name}</h3>'
+                                f'{format_bird_info(info)}'
+                                f'</div>',
+                                unsafe_allow_html=True
+                            )
+                        else:
+                            st.warning(f"Could not retrieve information for {bird_name}")
+
+    else:
+        # Process video
+        with st.spinner("Processing video..."):
+            tfile = tempfile.NamedTemporaryFile(delete=False)
+            tfile.write(uploaded_file.read())
+
+            cap = cv2.VideoCapture(tfile.name)
+            stframe = st.empty()
+            detected_birds = set()
+            bird_info_dict = {}
+
+            # Display detected birds list at the top (dynamic updating)
+            birds_placeholder = st.empty()
+
+            # Video processing progress bar
+            progress_bar = st.progress(0)
+            total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+            current_frame = 0
+
+            while cap.isOpened():
+                ret, frame = cap.read()
+                if not ret:
+                    break
+
+                # Update progress
+                current_frame += 1
+                progress_value = min(current_frame / total_frames, 1.0)
+                progress_bar.progress(progress_value)
+
+                # Only process every nth frame for efficiency
+                if current_frame % 10 == 0:  # Process every 10th frame
+                    results = model(frame)
+                    annotated_frame = results[0].plot()
+                    annotated_frame = cv2.cvtColor(annotated_frame, cv2.COLOR_BGR2RGB)
+
+                    # Display the processed frame
+                    stframe.image(annotated_frame, caption="Processing Video...", use_container_width=True)
+
+                    # Detect new birds in this frame
+                    new_birds = set()
+                    if results[0].boxes:
+                        for box in results[0].boxes:
+                            class_id = int(box.cls)
+                            if class_id in model.names:
+                                bird_name = model.names[class_id]
+                                if bird_name not in detected_birds:
+                                    detected_birds.add(bird_name)
+                                    new_birds.add(bird_name)  # Track newly detected birds
+
+                    # Update bird list dynamically
+                    birds_placeholder.markdown(f'<p class="bird-count">Detected Bird(s): {", ".join(detected_birds)}</p>',
+                                            unsafe_allow_html=True)
+
+                    # Fetch & display info for newly detected birds immediately
+                    for bird_name in new_birds:
+                        info = query_bird_info(bird_name)
+                        bird_info_dict[bird_name] = info
+
+                        if info:
+                            st.markdown(
+                                f'<div class="info-box">'
+                                f'<h3 class="bird-name">{bird_name}</h3>'
+                                f'{format_bird_info(info)}'
+                                f'</div>',
+                                unsafe_allow_html=True
+                            )
+                        else:
+                            st.warning(f"Could not retrieve information for {bird_name}")
+
+            cap.release()
+            progress_bar.empty()
+
+
+class_type = st.selectbox(
+    "If you want to know more about a specific bird, select the name of bird:",
+    [None,'Black footed Albatros',
+ 'Laysan Albatros',
+ 'Sooty Albatros',
+ 'Groove billed Ani',
+ 'Crested Aukle',
+ 'Least Aukle',
+ 'Parakeet Aukle',
+ 'Rhinoceros Aukle',
+ 'Brewer Blackbird',
+ 'Red winged Blackbird',
+ 'Rusty Blackbird',
+ 'Yellow headed Blackbird',
+ 'Bobolink',
+ 'Indigo Bunting',
+ 'Lazuli Bunting',
+ 'Painted Bunting',
+ 'Cardinal',
+ 'Spotted Catbird',
+ 'Gray Catbird',
+ 'Yellow breasted Chat',
+ 'Eastern Towhee',
+ 'Chuck will Widow',
+ 'Brandt Cormorant',
+ 'Red faced Cormorant',
+ 'Pelagic Cormorant',
+ 'Bronzed Cowbird',
+ 'Shiny Cowbird',
+ 'Brown Creeper',
+ 'American Crow',
+ 'Fish Crow',
+ 'Black billed Cuckoo',
+ 'Mangrove Cuckoo',
+ 'Yellow billed Cuckoo',
+ 'Gray crowned Rosy Finch',
+ 'Purple Finch',
+ 'Northern Flicker',
+ 'Acadian Flycatcher',
+ 'Great Crested Flycatcher',
+ 'Least Flycatcher',
+ 'Olive sided Flycatcher',
+ 'Scissor tailed Flycatcher',
+ 'Vermilion Flycatcher',
+ 'Yellow bellied Flycatcher',
+ 'Frigatebird',
+ 'Northern Fulmar',
+ 'Gadwall',
+ 'American Goldfinch',
+ 'European Goldfinch',
+ 'Boat tailed Grackle',
+ 'Eared Grebe',
+ 'Horned Grebe',
+ 'Pied billed Grebe',
+ 'Western Grebe',
+ 'Blue Grosbeak',
+ 'Evening Grosbeak',
+ 'Pine Grosbeak',
+ 'Rose breasted Grosbeak',
+ 'Pigeon Guillemot',
+ 'California Gull',
+ 'Glaucous winged Gull',
+ 'Heermann Gull',
+ 'Herring Gull',
+ 'Ivory Gull',
+ 'Ring billed Gull',
+ 'Slaty backed Gull',
+ 'Western Gull',
+ 'Anna Hummingbird',
+ 'Ruby throated Hummingbird',
+ 'Rufous Hummingbird',
+ 'Green Violetear',
+ 'Long tailed Jaeger',
+ 'Pomarine Jaeger',
+ 'Blue Jay',
+ 'Florida Jay',
+ 'Green Jay',
+ 'Dark eyed Junco',
+ 'Tropical Kingbird',
+ 'Gray Kingbird',
+ 'Belted Kingfisher',
+ 'Green Kingfisher',
+ 'Pied Kingfisher',
+ 'Ringed Kingfisher',
+ 'White breasted Kingfisher',
+ 'Red legged Kittiwake',
+ 'Horned Lark',
+ 'Pacific Loon',
+ 'Mallard',
+ 'Western Meadowlark',
+ 'Hooded Merganser',
+ 'Red breasted Merganser',
+ 'Mockingbird',
+ 'Nighthawk',
+ 'Clark Nutcracker',
+ 'White breasted Nuthatch',
+ 'Baltimore Oriole',
+ 'Hooded Oriole',
+ 'Orchard Oriole',
+ 'Scott Oriole',
+ 'Ovenbird',
+ 'Brown Pelican',
+ 'White Pelican',
+ 'Western Wood Pewee',
+ 'Sayornis',
+ 'American Pipit',
+ 'Whip poor Will',
+ 'Horned Puffin',
+ 'Common Raven',
+ 'White necked Raven',
+ 'American Redstart',
+ 'Geococcyx',
+ 'Loggerhead Shrike',
+ 'Great Grey Shrike',
+ 'Baird Sparrow',
+ 'Black throated Sparrow',
+ 'Brewer Sparrow',
+ 'Chipping Sparrow',
+ 'Clay colored Sparrow',
+ 'House Sparrow',
+ 'Field Sparrow',
+ 'Fox Sparrow',
+ 'Grasshopper Sparrow',
+ 'Harris Sparrow',
+ 'Henslow Sparrow',
+ 'Le Conte Sparrow',
+ 'Lincoln Sparrow',
+ 'Nelson Sharp tailed Sparrow',
+ 'Savannah Sparrow',
+ 'Seaside Sparrow',
+ 'Song Sparrow',
+ 'Tree Sparrow',
+ 'Vesper Sparrow',
+ 'White crowned Sparrow',
+ 'White throated Sparrow',
+ 'Cape Glossy Starling',
+ 'Bank Swallow',
+ 'Barn Swallow',
+ 'Cliff Swallow',
+ 'Tree Swallow',
+ 'Scarlet Tanager',
+ 'Summer Tanager',
+ 'Artic Tern',
+ 'Black Tern',
+ 'Caspian Tern',
+ 'Common Tern',
+ 'Elegant Tern',
+ 'Forsters Tern',
+ 'Least Tern',
+ 'Green tailed Towhee',
+ 'Brown Thrasher',
+ 'Sage Thrasher',
+ 'Black capped Vireo',
+ 'Blue headed Vireo',
+ 'Philadelphia Vireo',
+ 'Red eyed Vireo',
+ 'Warbling Vireo',
+ 'White eyed Vireo',
+ 'Yellow throated Vireo',
+ 'Bay breasted Warbler',
+ 'Black and white Warbler',
+ 'Black throated Blue Warbler',
+ 'Blue winged Warbler',
+ 'Canada Warbler',
+ 'Cape May Warbler',
+ 'Cerulean Warbler',
+ 'Chestnut sided Warbler',
+ 'Golden winged Warbler',
+ 'Hooded Warbler',
+ 'Kentucky Warbler',
+ 'Magnolia Warbler',
+ 'Mourning Warbler',
+ 'Myrtle Warbler',
+ 'Nashville Warbler',
+ 'Orange crowned Warbler',
+ 'Palm Warbler',
+ 'Pine Warbler',
+ 'Prairie Warbler',
+ 'Prothonotary Warbler',
+ 'Swainson Warbler',
+ 'Tennessee Warbler',
+ 'Wilson Warbler',
+ 'Worm eating Warbler',
+ 'Yellow Warbler',
+ 'Northern Waterthrush',
+ 'Louisiana Waterthrush',
+ 'Bohemian Waxwing',
+ 'Cedar Waxwing',
+ 'American Three toed Woodpecker',
+ 'Pileated Woodpecker',
+ 'Red bellied Woodpecker',
+ 'Red cockaded Woodpecker',
+ 'Red headed Woodpecker',
+ 'Downy Woodpecker',
+ 'Bewick Wren',
+ 'Cactus Wren',
+ 'Carolina Wren',
+ 'House Wren',
+ 'Marsh Wren',
+ 'Rock Wren',
+ 'Winter Wren',
+ 'Common Yell'],
+    key="Class Type"
+)
+
+def query_huggingface(prompt, bird_name):
+    system_prompt = (
+        f"You will only answer questions related to the birds listed below. "
+        f"If the question is about a bird not in the list, respond with 'I can only provide information about the detected birds.'\n\n"
+        f"List of detected birds: {bird_name}\n\n"
+        f"Now, answer the following question based only on this list: {prompt}"
+    )
+    payload = {"inputs": system_prompt, "parameters": {"temperature": 0.8, "max_length": 100}}
+    response = requests.post(API_URL, headers=headers, json=payload)
+    if response.status_code == 200:
+        generated_text = response.json()[0]["generated_text"]
+        return generated_text.replace(system_prompt, "").strip()
+    else:
+        return "Error: Unable to fetch response."
+    
+# Sidebar
+st.sidebar.title("Have any question? Ask me!")
+user_input = st.sidebar.text_input("You:", key="user_input")
+if st.sidebar.button("Send") and user_input:
+    if bird_name or class_type is not None:
+        response = query_huggingface(user_input, class_type or bird_name)
+        st.sidebar.write("**Bot:**", response)
+    else:
+        print("Please select a class ")
+
+st.markdown("""
+            ### Help:
+            - Upload an image or videos for detecting birds. After detection, information will be generated.
+            - Have further questions, select the bird name from drop down menu and ask the bot from sidebar.
+            """)

requirements.txt

@@ -0,0 +1,6 @@
+ultralytics
+streamlit==1.35.0
+requests
+opencv-python
+pillow
+numpy