--- title: Farm Segmentation API emoji: 🏞️ colorFrom: green colorTo: blue sdk: gradio sdk_version: 4.28.3 app_file: app.py pinned: false license: apache-2.0 short_description: AI-powered agricultural image segmentation and land analysis --- # 🏞️ Farm Segmentation API Advanced agricultural image segmentation using SegFormer models for precise field and crop analysis. ## 🎯 Capabilities - **Semantic Segmentation**: Pixel-level classification of agricultural scenes - **Agricultural Categories**: Soil, vegetation, water, buildings, equipment - **Composition Analysis**: Percentage breakdown of field components - **Multi-Resolution**: Support for different accuracy/speed tradeoffs ## 🤖 Models - **SegFormer B0**: Fastest processing, basic accuracy - **SegFormer B1**: Balanced performance (recommended) - **SegFormer B2**: Highest accuracy, slower processing ## 📡 API Usage ### Python ```python import requests import base64 def segment_farm_image(image_path, model="segformer_b1"): with open(image_path, "rb") as f: image_b64 = base64.b64encode(f.read()).decode() response = requests.post( "https://YOUR-USERNAME-farm-segmentation.hf.space/api/predict", json={"data": [image_b64, model]} ) return response.json() result = segment_farm_image("field_image.jpg") print(result) ``` ## 📊 Response Format ```json { "segments_detected": 8, "segments": [ { "class": "grass", "agricultural_category": "vegetation", "pixel_count": 145632, "percentage": 35.2, "label_id": 9 }, { "class": "soil", "agricultural_category": "soil", "pixel_count": 98234, "percentage": 23.7, "label_id": 12 } ], "processing_time": 2.1 } ``` ## 🌾 Agricultural Categories - **soil**: Ground, dirt, earth, mud - **vegetation**: Crops, grass, trees, plants - **water**: Irrigation channels, ponds, rivers - **building**: Barns, greenhouses, structures - **equipment**: Tractors, machinery, tools - **other**: Roads, sky, uncategorized objects