| import requests |
| import os |
|
|
| |
| |
| API_URL = "https://api-inference.huggingface.co/models/microsoft/resnet-50" |
|
|
| def classify_garment(image_path: str): |
| """ |
| Classifies a garment image using Hugging Face API with Filename Fallback. |
| """ |
| |
| |
| filename = os.path.basename(image_path).lower() |
| bottom_keywords = ["jean", "denim", "trouser", "pant", "skirt", "short", "legging", "sweatpant", "trunks"] |
| shoe_keywords = ["shoe", "sneaker", "boot", "sandal", "heel", "loafer", "clog"] |
| top_keywords = ["shirt", "jersey", "tee", "top", "blouse", "sweater", "cardigan", "jacket", "coat", "hoodie", "vest"] |
| |
| fallback_category = "top" |
| fallback_desc = "Uploaded Item" |
| |
| if any(k in filename for k in bottom_keywords): |
| fallback_category = "bottom" |
| fallback_desc = filename.split('.')[0].replace('_', ' ').title() |
| print(f"DEBUG: Filename '{filename}' matches BOTTOM keywords.") |
| elif any(k in filename for k in shoe_keywords): |
| fallback_category = "shoes" |
| fallback_desc = filename.split('.')[0].replace('_', ' ').title() |
| print(f"DEBUG: Filename '{filename}' matches SHOES keywords.") |
| elif any(k in filename for k in top_keywords): |
| fallback_category = "top" |
| fallback_desc = filename.split('.')[0].replace('_', ' ').title() |
| print(f"DEBUG: Filename '{filename}' matches TOP keywords.") |
| |
| |
| token = os.environ.get("HF_TOKEN") |
| if not token and os.path.exists("hf_token.txt"): |
| with open("hf_token.txt", "r") as f: |
| token = f.read().strip() |
| |
| if not token: |
| print("Warning: No HF Token. Using filename fallback.") |
| return fallback_category, fallback_desc, "untagged" |
|
|
| headers = {"Authorization": f"Bearer {token}"} |
| |
| try: |
| with open(image_path, "rb") as f: |
| data = f.read() |
| |
| print(f"Calling HF API ({API_URL})...") |
| response = requests.post(API_URL, headers=headers, data=data, timeout=5) |
| |
| if response.status_code != 200: |
| print(f"HF API Error: {response.status_code}. Using fallback.") |
| return fallback_category, fallback_desc, "api-error" |
| |
| predictions = response.json() |
| |
| if not predictions or not isinstance(predictions, list): |
| return fallback_category, fallback_desc, "api-unknown" |
| |
| top_prediction = predictions[0] |
| label = top_prediction.get('label', '').lower() |
| score = top_prediction.get('score', 0) |
| |
| print(f"AI Classification: '{label}' ({score:.2f})") |
| |
| |
| category = "top" |
| description = label.split(',')[0].title() |
| |
| if any(k in label for k in bottom_keywords): |
| category = "bottom" |
| elif any(k in label for k in shoe_keywords): |
| category = "shoes" |
| |
| |
| if "jersey" in label or "tee" in label: |
| description = "T-Shirt" |
| elif "jean" in label: |
| description = "Denim Jeans" |
| |
| return category, description, label |
| |
| except Exception as e: |
| print(f"Classification Failed: {e}. Using fallback.") |
| return fallback_category, fallback_desc, "error" |
|
|
