I need to find out all pools that are outside of the city borders/in open countryside in Germany in the Postcodes: 79189, 79194, 79199, 79206, 79219, 79224, 79227, 79232, 79235, 79238, 79241, 79244, 79249, 79252, 79254, 79256, 79258, 79268, 79271, 79274, 79280, 79282, 79283, 79285, 79286, 79288, 79289, 79291, 79292, 79294, 79295, 79299, 79356, 79379, 79395, 79410, 79423, 79424, 79426, 79427, 79822, 79843, 79853, 79856, 79859, 79868, 79871, 79874, 79877 The images can be found here publicly https://opengeodata.lgl-bw.de/#/ Ideally you programm an AI tool with Phyton. The core goal is to analyse geographic patterns—specifically, to locate and classify private and public pools, distinguish them from similar water bodies, and output their coordinates and confidence scores. Here are instructions of someone who has done it in the past: https://developers.arcgis.com/python/latest/samples/detecting-swimming-pools-using-satellite-image-and-deep-learning/?utm_source=chatgpt.com If you have experience with computer vision on aerial or satellite imagery, let’s make this happen. I need a list of post adresses delivered by April 20th 7am CET