adding basic classification structure

.gitignore

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+.env
+__pycache__
+venv
+.DS_Store

app.py

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+import gradio as gr
+import open_clip
+import torch
+import requests
+import numpy as np
+from PIL import Image
+from io import BytesIO
+from items import ecommerce_items
+import os
+from dotenv import load_dotenv
+
+# Load environment variables from the .env file
+load_dotenv()
+
+# Sidebar content
+sidebar_markdown = """
+
+Note, this demo can classify 200 items. If you didn't find what you're looking for, reach out to us on our [Community](https://join.slack.com/t/marqo-community/shared_invite/zt-2iab0260n-QJrZLUSOJYUifVxf964Gdw) and request an item to be added.
+
+## Documentation
+📚 [Blog Post]()
+
+📝 [Use Case Blog Post]()
+
+## Code
+💻 [GitHub Repo]()
+
+🤝 [Google Colab]()
+
+🤗 [Hugging Face Collection]()
+
+## Citation
+If you use Marqo-Ecommerce-L or Marqo-Ecommerce-B, please cite us:
+```
+
+```
+"""
+
+from huggingface_hub import login
+
+# Get your Hugging Face API key (ensure it is set in your environment variables)
+api_key = os.getenv("HF_API_TOKEN")
+
+if api_key is None:
+    raise ValueError("Hugging Face API key not found. Please set the 'HF_API_TOKEN' environment variable.")
+
+# Login using the token
+login(token=api_key)
+
+# Initialize the model and tokenizer
+def load_model(progress=gr.Progress()):
+    progress(0, "Initializing model...")
+    model_name = 'hf-hub:Marqo/marqo-ecommerce-embeddings-B'
+    model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms(model_name)
+    
+    progress(0.5, "Loading tokenizer...")
+    tokenizer = open_clip.get_tokenizer(model_name)
+    
+    text = tokenizer(ecommerce_items)
+    
+    progress(0.75, "Encoding text features...")
+    with torch.no_grad(), torch.amp.autocast('cuda'):
+        text_features = model.encode_text(text)
+        text_features /= text_features.norm(dim=-1, keepdim=True)
+    
+    progress(1.0, "Model loaded successfully!")
+    
+    return model, preprocess_val, text_features
+
+# Load model and prepare interface
+model, preprocess_val, text_features = load_model()
+
+# Prediction function
+def predict(image, url):
+    if url:
+        response = requests.get(url)
+        image = Image.open(BytesIO(response.content))
+    
+    processed_image = preprocess_val(image).unsqueeze(0)
+
+    with torch.no_grad(), torch.amp.autocast('cuda'):
+        image_features = model.encode_image(processed_image)
+        image_features /= image_features.norm(dim=-1, keepdim=True)
+
+        text_probs = (100 * image_features @ text_features.T).softmax(dim=-1)
+        
+        sorted_confidences = sorted(
+            {ecommerce_items[i]: float(text_probs[0, i]) for i in range(len(ecommerce_items))}.items(), 
+            key=lambda x: x[1], 
+            reverse=True
+        )
+        top_10_confidences = dict(sorted_confidences[:10])
+        
+    return image, top_10_confidences
+
+# Clear function
+def clear_fields():
+    return None, ""
+
+# Gradio interface
+title = "Ecommerce Item Classifier with Marqo-Ecommerce Embedding Models"
+description = "Upload an image or provide a URL of a fashion item to classify it using Marqo-Ecommerce Models!"
+
+examples = [
+    ["images/laptop.png", "Laptop"],
+    ["images/grater.png", "Grater"],
+    ["images/flip-flops.jpg", "Flip Flops"],
+    ["images/bike-helmet.png", "Bike Helmet"],
+    ["images/sleeping-bag.png", "Sleeping Bag"],
+    ["images/cutting-board.png", "Cutting Board"],
+    ["images/iron.png", "Iron"],
+    ["images/coffee.png", "Coffee"],
+]
+
+with gr.Blocks(css="""
+    .remove-btn {
+        font-size: 24px !important; /* Increase the font size of the cross button */
+        line-height: 24px !important;
+        width: 30px !important; /* Increase the width */
+        height: 30px !important; /* Increase the height */
+    }
+""") as demo:
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown(f"# {title}")
+            gr.Markdown(description)
+            gr.Markdown(sidebar_markdown)
+            gr.Markdown(" ", elem_id="vertical-line")  # Add an empty Markdown with a custom ID
+        with gr.Column(scale=2):
+            input_image = gr.Image(type="pil", label="Upload Fashion Item Image", height=312)
+            input_url = gr.Textbox(label="Or provide an image URL")
+            with gr.Row():
+                predict_button = gr.Button("Classify")
+                clear_button = gr.Button("Clear")
+            gr.Markdown("Or click on one of the images below to classify it:")
+            gr.Examples(examples=examples, inputs=input_image)
+            output_label = gr.Label(num_top_classes=6)
+            predict_button.click(predict, inputs=[input_image, input_url], outputs=[input_image, output_label])
+            clear_button.click(clear_fields, outputs=[input_image, input_url])
+
+# Launch the interface
+demo.launch()

items.py

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+ecommerce_items = [
+    "laptop", "smartphone", "tablet", "headphones", "smartwatch", "camera", 
+    "printer", "gaming console", "TV", "keyboard", "mouse", "monitor", 
+    "external hard drive", "USB drive", "memory card", "router", "modem", 
+    "vacuum cleaner", "washing machine", "refrigerator", "microwave", 
+    "air conditioner", "toaster", "blender", "coffee maker", "kitchen appliance", 
+    "furniture", "mattress", "bedding", "shoes", "clothing", "handbag", 
+    "watch", "sunglasses", "cosmetics", "skincare", "perfume", "books", 
+    "toys", "video games", "jewelry", "fitness equipment", "bike", "sports gear", 
+    "pet supplies", "office supplies", "stationery", "gardening tools", 
+    "power tools", "home decor", "art supplies", "musical instruments", 
+    "baby products", "diapers", "groceries", "snacks", "health supplements", 
+    "vitamins", "medications", "cleaning supplies", "water bottle", "backpack", 
+    "notebook", "planner", "pen", "pencil", "water filter", "electric kettle", 
+    "hair dryer", "hair straightener", "shaving kit", "toothbrush", "toothpaste", 
+    "soap", "shampoo", "conditioner", "razor", "deodorant", "body lotion", 
+    "hand sanitizer", "first aid kit", "flashlight", "batteries", "extension cord", 
+    "light bulb", "fan", "heater", "humidifier", "dehumidifier", "iron", 
+    "clothes steamer", "vacuum bags", "toolbox", "drill", "screwdriver", 
+    "hammer", "nails", "tape measure", "wrench", "pliers", "ladder", "paint", 
+    "paintbrush", "roller", "drop cloth", "caulk", "sealant", "screws", "bolts", 
+    "nuts", "faucet", "showerhead", "toilet paper", "paper towels", "trash bags", 
+    "cleaning cloth", "disinfectant wipes", "mop", "broom", "dustpan", 
+    "scrubbing brush", "laundry detergent", "fabric softener", "dryer sheets", 
+    "dish soap", "sponge", "cutlery", "plates", "bowls", "cups", "glasses", 
+    "wine glasses", "baking sheets", "pots", "pans", "cutting board", 
+    "kitchen knives", "grater", "peeler", "mixing bowls", "measuring cups", 
+    "measuring spoons", "oven mitts", "apron", "spatula", "whisk", "can opener", 
+    "wine opener", "dish rack", "salt", "pepper", "herbs", "spices", "oil", 
+    "vinegar", "sugar", "flour", "rice", "pasta", "cereal", "bread", 
+    "cookies", "crackers", "chips", "coffee", "tea", "juice", "soda", 
+    "water", "wine", "beer", "whiskey", "vodka", "rum", "champagne", 
+    "cocktail shaker", "ice tray", "pizza cutter", "cheese slicer", 
+    "tupperware", "food storage bags", "aluminum foil", "plastic wrap", 
+    "parchment paper", "disposable plates", "disposable cups", "plastic utensils", 
+    "grill", "BBQ tools", "charcoal", "firewood", "cooler", "picnic basket", 
+    "lawn chair", "outdoor furniture", "hammock", "tent", "sleeping bag", 
+    "camping stove", "lantern", "fishing rod", "bicycle helmet", "running shoes", 
+    "yoga mat", "dumbbells", "jump rope", "resistance bands", "treadmill", 
+    "elliptical machine", "stationary bike", "protein powder", "energy bars", 
+    "water bottle", "goggles", "swimsuit", "sunscreen", "insect repellent", 
+    "beach towel", "sandals", "flip flops", "suitcase", "travel pillow", 
+    "passport holder", "luggage tag", "camera tripod", "memory card reader", 
+    "portable charger", "phone case", "screen protector", "sunhat", "hat", "trousers",
+    "t-shirt", "shirt", "socks", "shoes",
+]

requirements.txt

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+open_clip_torch
+transformers