class MapillaryLocationDownloader: def __init__(self): self.location_saver = LocationSaver(SAVE_PATH) self.map_api = Mapillary( "dThHWFVHb0dNdnIyb0xDbm11NHVadzo1MjgxMWMyZDNjOTM0YjAy") def download_location(self, location_data): image_key = location_data["properties"]["key"] lon, lat = location_data["geometry"]["coordinates"] direction = location_data["properties"]["ca"] image_file_path = self.location_saver.save_new_location( lat, lon, direction) if os.path.exists(image_file_path): os.remove(image_file_path) download_image_by_key(image_key, IMAGE_WIDTH, image_file_path) format_image(image_file_path) def download_randomly_in_bounding_box(self, boundingbox, num): if num == 0: return 0 lat1, lon1, lat2, lon2 = boundingbox bbox = ",".join(map(lambda x: "%.6f" % x, [lon1, lat1, lon2, lat2])) try: res = self.map_api.search_images( bbox=bbox, per_page=MAX_PER_REQUEST) except: print(bbox) raise "Error while searching images in Mapillary" if "features" not in res: print(res) res_locations = res["features"] if len(res_locations) == MAX_PER_REQUEST and num > 1: # Too many locations, splitting up query to spread out images mid_lat = (lat1+lat2)/2 mid_lon = (lon1+lon2)/2 new_bounding_boxes = [] new_bounding_boxes.append([lat1, lon1, mid_lat, mid_lon]) new_bounding_boxes.append([mid_lat, lon1, lat2, mid_lon]) new_bounding_boxes.append([lat1, mid_lon, mid_lat, lon2]) new_bounding_boxes.append([mid_lat, mid_lon, lat2, lon2]) random.shuffle(new_bounding_boxes) has_downloaded = 0 for i in range(4): has_downloaded += self.download_randomly_in_bounding_box( new_bounding_boxes[i], (num-has_downloaded)//(4-i)) return has_downloaded num = min(len(res_locations), num) for location_data in random.choices(res_locations, k=num): self.download_location(location_data) return num
def test_search_images(self): map = Mapillary(API_KEY) bbox = "16.430300,7.241686,16.438757,7.253186" per_page = 1 raw_json = map.search_images(bbox=bbox, per_page=per_page) features_json = raw_json['features'] # The json's is in a list for features in features_json: coordinate = features['geometry']['coordinates'] self.assertEqual([16.432976, 7.249027], coordinate)
def download_mapillary(self, mapillary_key, start=0, end=-1): """ Downloads Mapillary images of points from a ArcGis layer :param mapillary_key: Mapillary API key :type mapillary_key: str :param start: index of the feature of the layer from where download starts :type start: int :param end: index of the feature of the layer where download ends :type end: int """ # Initialization of variables self.nb_mapillary_jpg = 0 self.nb_mapillary_panos = 0 cmp_err = 0 err_list = [] # Creation of directory self.mapillary_dir = safe_folder_creation(self.mapillary_dir) self.mapillary_dir_pano = safe_folder_creation(self.mapillary_dir_pano) # Convert layer file ds = ogr.Open(self.layer_path) layer = ds.GetLayer() # Determine the number of locations to download loc_max = len(layer) if start < end < len(layer): stop = end else: stop = loc_max n_loc = stop - start # Create a Mapillary Object mapillary = Mapillary(mapillary_key) # Display advancement of downloading pbar = progressbar.ProgressBar() for i in pbar(range(start, stop)): # Get location feature = layer[i] lon = feature.GetGeometryRef().GetX() lat = feature.GetGeometryRef().GetY() close_to = "{},{}".format(lon, lat) # Catch metadata search errors try: raw_json = mapillary.search_images(closeto=close_to, per_page=1, radius=10) raw_json_pano = mapillary.search_images(closeto=close_to, per_page=1, radius=10, pano="true") except Exception as err: print(err) print("Error during metadata search on feature {}, lat = {}, lon = {} ".format(i, lat, lon)) cmp_err += 1 err_list.append(i) continue # Check if there is a image at this location and download it try: if len(raw_json['features']): image_key = raw_json['features'][0]['properties']['key'] image_date = raw_json['features'][0]['properties']['captured_at'][:-5] image_date = image_date.replace(":", "-") image_lon = raw_json['features'][0]['geometry']['coordinates'][0] image_lat = raw_json['features'][0]['geometry']['coordinates'][1] image_lon = "{0:.6f}".format(image_lon) image_lat = "{0:.6f}".format(image_lat) image_filename = '{}_{}_{}_000_{}.jpg'.format(image_lon, image_lat, image_key, image_date) image_path = os.path.join(self.mapillary_dir, image_filename) download_image_by_key(image_key, 640, image_path) self.nb_mapillary_jpg += 1 except Exception as err: print(err) print("Error when downloading image on feature {}, lat = {}, lon = {} ".format(i, lat, lon)) cmp_err += 1 err_list.append(i) continue # Check if there is a pano at this location and download it try: if len(raw_json_pano['features']): pano_key = raw_json_pano['features'][0]['properties']['key'] pano_date = raw_json_pano['features'][0]['properties']['captured_at'][:-5] pano_date = pano_date.replace(":", "-") pano_lon = raw_json_pano['features'][0]['geometry']['coordinates'][0] pano_lat = raw_json_pano['features'][0]['geometry']['coordinates'][1] pano_lon = "{0:.6f}".format(pano_lon) pano_lat = "{0:.6f}".format(pano_lat) pano_filename = '{}_{}_{}_999_{}.jpg'.format(pano_lon, pano_lat, pano_key, pano_date) pano_path = os.path.join(self.mapillary_dir_pano, pano_filename) download_image_by_key(pano_key, 2048, pano_path) self.nb_mapillary_panos += 1 except Exception as err: print(err) print("Error when downloading panorama on feature {}, lat = {}, lon = {} ".format(i, lat, lon)) cmp_err += 1 err_list.append(i) continue # Display information print("Number of locations : {}".format(n_loc)) print("Number of images downloaded : {}".format(self.nb_mapillary_jpg)) print("Number of panoramas downloaded : {}".format(self.nb_mapillary_panos)) print("Number of errors caught : {}".format(cmp_err)) print("List of features index with errors : {}".format(err_list))
# This example uses the function search_images to do a query based # on the variables that are declared below. from pymapillary import Mapillary from pymapillary.utils import * # Every parameter that can be passed in to this search function # Plug and play as you please bbox = "16.430300,7.241686,16.438757,7.253186" # minx,miny,maxx,maxy closeto = "13.0006076843,55.6089295863" #longitude, latitude end_time = "2016-03-14T13:44:37.206Z" #must be a valid ISO 8601 date image_keys = "LwrHXqFRN_pszCopTKHF_Q, Aufjv2hdCKwg9LySWWVSwg" lookat = "12.9981086701,55.6075236275" #longitude, latitude pano = "true" # or "false" it has to be lower cased per_page = 1 # default is 200 project_keys = "HvOINSQU9fhnCQTpm0nN7Q" #json is userkey this worked too? PSaXX2JB7snjFyHJF-Rb1A for sequence key? JnLaPNIam8LFNZL1Zh9bPQ all keys work? radius = 100 # In meters sequence_keys = "PSaXX2JB7snjFyHJF-Rb1A, LMlIPUNhaj24h_q9v4ArNw" start_time = "2016-03-14T13:44:37.206Z" #start_time" must be a valid ISO 8601 date userkeys = "HvOINSQU9fhnCQTpm0nN7Q" usernames = "maning" #example user name # Create a Mapillary Object map = Mapillary("insert client id here") raw_json = map.search_images(bbox=bbox, per_page=per_page) print(raw_json) # Download the beautified json for debugging return_json_file(raw_json, "../sample_json_output/search_images_example.json")
def query_only_id_bboxes(city, enlarge=True): # get coordinates of city, request ot open-street-map if enlarge: top, right, bot, left = getCityLimitsBoundingBox(city, 0.3) else: top, right, bot, left = getCityLimitsBoundingBox(city) left_most = float(left[0]) right_most = float(right[0]) top_most = float(top[1]) bot_most = float(bot[1]) # Get the maximum direction and center center_lon = (left_most + right_most) / 2 center_lat = (top_most + bot_most) / 2 d = latlongdist(left_most, top_most, right_most, bot_most) * 1000 os.makedirs(cfg.mapillary["data_dir"], exist_ok=True) city_dir_path = os.path.join(cfg.mapillary["data_dir"], city) os.makedirs(city_dir_path, exist_ok=True) seq_city_dir_path = os.path.join(city_dir_path, "seq") os.makedirs(seq_city_dir_path, exist_ok=True) img_city_dir_path = os.path.join(city_dir_path, "img") os.makedirs(img_city_dir_path, exist_ok=True) imgdata_city_dir_path = os.path.join(city_dir_path, "img_data") os.makedirs(imgdata_city_dir_path, exist_ok=True) # Create a Mapillary Object map = Mapillary(cfg.mapillary["api_key"]) bbox = str(left_most) + "," + str(bot_most) + "," + str( right_most) + "," + str(top_most) if not path.exists(os.path.join(city_dir_path, city + "_result.json")): data, next_img = map.search_images(bbox=bbox, per_page=cfg.mapillary["per_page"]) data = aggregate(data, next_img, cfg.mapillary["per_page"], map) # Download the beautified json for debugging return_json_file(data, os.path.join(city_dir_path, city + "_result.json")) else: data = json.load( open(os.path.join(city_dir_path, city + "_result.json"))) nodes = [] for idx, f in enumerate(data["features"]): if not 'sequence_key' in f["properties"]: print('Skip ', str(idx), '/', len(data["features"])) continue print('Processing ', str(idx), '/', len(data["features"]), ' - ', f["properties"]["sequence_key"]) seq_raw_path = os.path.join(seq_city_dir_path, f["properties"]["sequence_key"] + ".json") if not path.exists(seq_raw_path): try: print('Pulling ', str(idx), '/', len(data["features"]), ' - ', f["properties"]["sequence_key"]) seq_raw_json = map.get_sequence_by_key( key=f["properties"]["sequence_key"]) except: print('Failed to acuire, skipping') continue return_json_file(seq_raw_json, seq_raw_path) else: print('Loading ', str(idx), '/', len(data["features"]), ' - ', f["properties"]["sequence_key"]) seq_raw_json = json.load(open(seq_raw_path)) for i, img_id in enumerate(seq_raw_json["properties"] ["coordinateProperties"]["image_keys"]): # Check is in target area lon, lat = seq_raw_json["geometry"]["coordinates"][i] img_path = os.path.join(img_city_dir_path, img_id + ".jpg") img_data_path = os.path.join(imgdata_city_dir_path, img_id + ".json") if not path.exists(img_path): print(' Pulling', img_id) download_image_by_key(img_id, 2048, img_path) if not path.exists(img_data_path): # Organise a custom Json to massively redundant but abstracts sequences img_data = {} img_data["coordinate_location"] = seq_raw_json["geometry"][ "coordinates"][i] img_data["file_path"] = img_path img_data["image_key"] = img_id img_data["camera_make"] = seq_raw_json["properties"][ "camera_make"] img_data["captured_at"] = seq_raw_json["properties"][ "captured_at"] img_data["created_at"] = seq_raw_json["properties"][ "created_at"] img_data["pano"] = seq_raw_json["properties"]["pano"] img_data["user_key"] = seq_raw_json["properties"]["user_key"] img_data["username"] = seq_raw_json["properties"]["username"] img_data["cas"] = seq_raw_json["properties"][ "coordinateProperties"]["cas"][i] with open(img_data_path, "w") as write_file: json.dump(img_data, write_file, indent=2) else: img_data = json.load(open(img_data_path)) # Add to Knowledge Graph keys = [] values = [] for k, v in img_data.items(): keys.append(k) values.append(v) nodes.append([keys, values]) return nodes