[test] set some logs ad debug
Browse files
src/io/coordinates_pixel_conversion.py
CHANGED
@@ -12,18 +12,18 @@ class PixelCoordinate(TypedDict):
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def get_latlng2pixel_projection(latlng: LatLngDict) -> PixelCoordinate:
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app_logger.
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app_logger.
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app_logger.
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try:
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sin_y: float = math.sin(latlng.lat * math.pi / 180)
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app_logger.
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sin_y = min(max(sin_y, -0.9999), 0.9999)
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app_logger.
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x = TILE_SIZE * (0.5 + latlng.lng / 360)
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app_logger.
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y = TILE_SIZE * (0.5 - math.log((1 + sin_y) / (1 - sin_y)) / (4 * math.pi))
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app_logger.
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return {"x": x, "y": y}
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except Exception as e_get_latlng2pixel_projection:
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@@ -34,9 +34,9 @@ def get_latlng2pixel_projection(latlng: LatLngDict) -> PixelCoordinate:
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def get_point_latlng_to_pixel_coordinates(latlng: LatLngDict, zoom: int | float) -> PixelCoordinate:
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try:
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world_coordinate: PixelCoordinate = get_latlng2pixel_projection(latlng)
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app_logger.
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scale: int = pow(2, zoom)
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app_logger.
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return PixelCoordinate(
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x=math.floor(world_coordinate["x"] * scale),
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y=math.floor(world_coordinate["y"] * scale)
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@@ -53,13 +53,13 @@ def get_latlng_to_pixel_coordinates(
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zoom: int | float,
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k: str
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):
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app_logger.
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app_logger.
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latlng_map_origin_ne = get_point_latlng_to_pixel_coordinates(latlng_origin_ne, zoom)
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latlng_map_origin_sw = get_point_latlng_to_pixel_coordinates(latlng_origin_sw, zoom)
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latlng_map_current_point = get_point_latlng_to_pixel_coordinates(latlng_current_point, zoom)
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diff_coord_x = abs(latlng_map_origin_sw["x"] - latlng_map_current_point["x"])
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diff_coord_y = abs(latlng_map_origin_ne["y"] - latlng_map_current_point["y"])
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point = PixelCoordinate(x=diff_coord_x, y=diff_coord_y)
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app_logger.
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return point
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def get_latlng2pixel_projection(latlng: LatLngDict) -> PixelCoordinate:
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+
app_logger.debug(f"latlng: {type(latlng)}, value:{latlng}.")
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app_logger.debug(f'latlng lat: {type(latlng.lat)}, value:{latlng.lat}.')
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app_logger.debug(f'latlng lng: {type(latlng.lng)}, value:{latlng.lng}.')
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try:
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sin_y: float = math.sin(latlng.lat * math.pi / 180)
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app_logger.debug(f"sin_y, #1:{sin_y}.")
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sin_y = min(max(sin_y, -0.9999), 0.9999)
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app_logger.debug(f"sin_y, #2:{sin_y}.")
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x = TILE_SIZE * (0.5 + latlng.lng / 360)
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app_logger.debug(f"x:{x}.")
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y = TILE_SIZE * (0.5 - math.log((1 + sin_y) / (1 - sin_y)) / (4 * math.pi))
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app_logger.debug(f"y:{y}.")
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return {"x": x, "y": y}
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except Exception as e_get_latlng2pixel_projection:
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def get_point_latlng_to_pixel_coordinates(latlng: LatLngDict, zoom: int | float) -> PixelCoordinate:
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try:
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world_coordinate: PixelCoordinate = get_latlng2pixel_projection(latlng)
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+
app_logger.debug(f"world_coordinate:{world_coordinate}.")
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scale: int = pow(2, zoom)
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app_logger.debug(f"scale:{scale}.")
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return PixelCoordinate(
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x=math.floor(world_coordinate["x"] * scale),
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y=math.floor(world_coordinate["y"] * scale)
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zoom: int | float,
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k: str
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):
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app_logger.debug(f"latlng_origin - {k}: {type(latlng_origin_ne)}, value:{latlng_origin_ne}.")
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app_logger.debug(f"latlng_current_point - {k}: {type(latlng_current_point)}, value:{latlng_current_point}.")
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latlng_map_origin_ne = get_point_latlng_to_pixel_coordinates(latlng_origin_ne, zoom)
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latlng_map_origin_sw = get_point_latlng_to_pixel_coordinates(latlng_origin_sw, zoom)
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latlng_map_current_point = get_point_latlng_to_pixel_coordinates(latlng_current_point, zoom)
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diff_coord_x = abs(latlng_map_origin_sw["x"] - latlng_map_current_point["x"])
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diff_coord_y = abs(latlng_map_origin_ne["y"] - latlng_map_current_point["y"])
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point = PixelCoordinate(x=diff_coord_x, y=diff_coord_y)
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+
app_logger.debug(f"point type - {k}: {point}.")
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return point
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src/prediction_api/predictors.py
CHANGED
@@ -30,7 +30,7 @@ def samexporter_predict(bbox, prompt: list[dict], zoom: float, model_name: str =
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app_logger.info(f"img type {type(img)} with shape/size:{img.size}, matrix:{matrix}.")
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transform = get_affine_transform_from_gdal(matrix)
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app_logger.
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mask, n_predictions = get_raster_inference(img, prompt, models_instance, model_name)
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app_logger.info(f"created {n_predictions} masks, preparing conversion to geojson...")
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app_logger.info(f"img type {type(img)} with shape/size:{img.size}, matrix:{matrix}.")
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transform = get_affine_transform_from_gdal(matrix)
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app_logger.info(f"transform to consume with rasterio.shapes: {type(transform)}, {transform}.")
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mask, n_predictions = get_raster_inference(img, prompt, models_instance, model_name)
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app_logger.info(f"created {n_predictions} masks, preparing conversion to geojson...")
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