update RCA algo and set RELOAD in docker-compose to --reload (#78)

Co-authored-by: janf <[email protected]>

docker-compose.yml

@@ -16,6 +16,8 @@ services:
        - "./src/cogserver:/opt/server/cogserver"
     env_file:
       - ./gdal_rio.env
+    environment:
+      - RELOAD=--reload
     # the above env file contains the $PORT variable.
     ports:
       - "${PORT}:${PORT}"

src/cogserver/algorithms/rca.py

@@ -1,79 +1,101 @@
 from typing import Sequence
-
 import numpy
+from typing import List
 from pydantic import Field
 from rio_tiler.models import ImageData
-
 from titiler.core.algorithm.base import BaseAlgorithm
 
 
+
+
+
+
+
 class RapidChangeAssessment(BaseAlgorithm):
 
     title: str = "Rapid Change Assessment Tool"
-    description: str = "Quick assessment to detect changes by comparing two bands"
+    description: str = "Detect changes by subtracting relative radiances between two images taken between and after an event"
 
     """Rapid change assessment."""
     # parameters
-    threshold: float = Field(
-        0.8, ge=0.0, le=1.0,
-        title="Threshold(%)",
-        description="Threshold (%) to mask changes which is ranged between 0 and 1"
-    )
+    # threshold: float = Field(
+    #     default=0, ge=0.0, le=1.0,
+    #     title="Threshold(%)",
+    #     description="Only pixels with change/decrease above this threshold will be supplied"
+    # )
+
+    only_negative: bool = Field(
+        default=True,
+        title='Only negative',
+        description='Compute only pixels whose values have decreased between the two dates'
 
-    cloud_mask: bool = Field(
-        False,
-        title="Cloud mask",
-        description="If enabled, cloud will be removed masked by band 3 and band 4."
     )
 
-    cloud_mask_threshold: int = Field(
-        1,
+    # cloud_mask: bool = Field(
+    #     False,
+    #     title="Cloud mask",
+    #     description="If enabled, cloud will be removed masked by band 3 and band 4."
+    # )
+
+    cloud_mask_value: int = Field(
+        default=1,
+        ge=0,
+        le=5,
         title="Cloud mask threshold",
-        description="Remove cloud if band value is greater than this threshold"
+        description="Inclusive cloud threshold. Specifying a value results in considering all lower values",
+        options_descriptions = ['No clouds', 'Almost no clouds', 'Very few clouds', 'Partially cloudy', 'Cloudy', 'Very cloudy' ]
     )
 
+
+
     # metadata
     input_nbands: int = 2
-    input_description: str = "the first two bands will be used to compute change detection. " \
-                             "the last two bands will be used to mask the result. " \
-                             "The first two bands are required. "
+    input_description: str = "The bands that will be used to detect changes"
+    input_bands: List = [
+        {'title': 'Start date image', 'description': 'The image before the event',  'required':True},
+        {'title': 'End date image', 'description': 'The image after the event',  'required':True},
+        {'title': 'Start date cloud mask', 'description': 'The cloud mask of the image before the event',
+         'required': True},
+        {'title': 'End date cloud mask', 'description': 'The cloud mask of the image after the event',
+         'required': True},
+    ]
+
+    # input_second_image_title: str = 'Second image'
+    # input_second_image_description: str = 'The image after the event'
 
     output_nbands: int = 1
-    output_dtype: int = "uint8"
-    output_min: Sequence[int] = [0]
-    output_max: Sequence[int] = [1]
-    output_description: str = "Masked result which has changed greater than threshold"
+    output_dtype: int = "int8"
+    output_min: Sequence[int] = [-100]
+    output_max: Sequence[int] = [100]
+    output_description: str = "Pixels/locations whose values have decreased/changed"
 
     def __call__(self, img: ImageData) -> ImageData:
         """Rapid change assessment."""
-        b1 = img.array[0].astype("float16")
-        b2 = img.array[1].astype("float16")
-
-        diff = numpy.abs(b1 - b2)
-        total = numpy.abs(b1) + numpy.abs(b2)
-
-        # If the difference is more than threshold, return 1. Otherwise return 0
-        data = (diff / total > self.threshold)
-
-        # add additional mask condition to remove cloud
-        if self.cloud_mask and len(img.array) > 2:
-            # add the third band to mask
-            b3 = img.array[2].astype("uint8")
-            valid_mask = (b3 > self.cloud_mask_threshold)
-
-            if len(img.array) > 3:
-                # add the fourth band to mask if available
-                b4 = img.array[3].astype("uint8")
-                valid_mask = valid_mask | (b4 > self.cloud_mask_threshold)
-            arr = numpy.ma.masked_array(data, dtype=self.output_dtype, mask=valid_mask)
-        else:
-            arr = numpy.ma.masked_array(data, dtype=self.output_dtype)
-
-        bnames = img.band_names
+        b1 = img.array[0]
+        b2 = img.array[1]
+        b2 = b2 / b2.max()
+        b1 = b1 / b1.max()
+        valid_mask = (img.array[2].astype('uint8') > self.cloud_mask_value) | (img.array[3].astype('uint8') > self.cloud_mask_value)
+        diff = b2-b1
+        data = diff
+        v = .1
+        #v = data.ptp()*.1
+
+        datam = (data > -v) & (data < v)
+
+        if self.only_negative:
+            datam |= data>0
+
+
+        arr = numpy.ma.masked_array(data*100, dtype=self.output_dtype, mask=valid_mask | datam )
+
+        word = 'changes' if not self.only_negative else 'decrease'
+
         return ImageData(
             arr,
             assets=img.assets,
             crs=img.crs,
             bounds=img.bounds,
-            band_names=[f"(abs({bnames[1]} - {bnames[0]}) / ({bnames[1]} + {bnames[0]})) > {self.threshold}"],
+            band_names=[f"Relative {word} in pixels value"],
         )
+