first implementation of the microservice.

README.md

@@ -1,53 +1,20 @@
-# Create a new service (generic) template
-
-This repository contains the Python + FastAPI template to create a service
-without a model or from an existing model compatible with the Core engine.
-
-Please read the documentation at
-<https://docs.swiss-ai-center.ch/how-to-guides/how-to-create-a-new-service> to
-understand how to use this template.
-
-## Guidelines
-
-TODO: Add instructions on how to edit this template.
-
-### Publishing and deploying using a CI/CD pipeline
-
-This is the recommended way to publish and deploy your service if you have
-access to GitHub Actions or GitLab CI.
-
-TODO
-
-### Publishing and deploying manually
-
-This is the recommended way to publish and deploy your service if you do not
-have access to GitHub Actions or GitLab CI or do not want to use these services.
-
-TODO
-
-## Checklist
-
-These checklists allow you to ensure everything is set up correctly.
-
-### Common tasks
-
-- [ ] Rename the project in the [`pyproject.toml`](./pyproject.toml) file
-- [x] Add files that must be ignored to the [`.gitignore`](.gitignore) configuration file
-- [ ] TODO
-
-### Publishing and deploying using a CI/CD pipeline
-
-> [!NOTE]  
-> This checklist is specific to the _Publishing and deploying using a CI/CD
-> pipeline_ section.
-
-- [x] Add the environment variables
-- [ ] TODO
-
-### Publishing and deploying manually
-
-> [!NOTE]  
-> This checklist is specific to the _Publishing and deploying manually_ section.
-
-- [x] Edit the [`.env`](.env) configuration file
-- [ ] TODO
+# Image Draw Bounding Boxes
+This microservice draws boxes on an image. It is intended to work with the
+text recognition OCR service. The bounding boxes are passed in a JSON file that corresponds to the output of
+the text recognition service. Namely, it must have the following structure:
+```
+{"boxes":[
+    "position":{
+        "left": ...,
+        "top": ...,
+        "width": ...,
+        "height": ...,
+    },
+    {"position": ...},
+    ...
+]}
+```
+Where the values in "left", "top", "width" and "height" are given in pixels. 
+The bounding boxes are drawn as red unfilled rectangles at the coordinates specified by the 4 fields above.
+
+The JSON file may contain additional fields; they will be ignored.

pyproject.toml

@@ -1,5 +1,5 @@
 [project]
-name = "service" # Edit this and remove comment
+name = "image-draw-bounding-boxes"
 
 [tool.pytest.ini_options]
 pythonpath = [".", "src"]

requirements-all.txt

@@ -0,0 +1,57 @@
+aiobotocore==2.12.1
+aiofiles==23.2.1
+aiohappyeyeballs==2.4.0
+aiohttp==3.10.5
+aioitertools==0.11.0
+aiosignal==1.3.1
+annotated-types==0.7.0
+anyio==4.4.0
+async-timeout==4.0.3
+attrs==24.2.0
+botocore==1.34.51
+certifi==2024.7.4
+click==8.1.7
+common_code @ git+https://github.com/swiss-ai-center/common-code.git@e8bfec8bc00995aa2a0b022bcac03780d38856af
+coverage==7.6.1
+dnspython==2.6.1
+email_validator==2.1.1
+exceptiongroup==1.2.2
+fastapi==0.110.0
+flake8==7.0.0
+frozenlist==1.4.1
+h11==0.14.0
+httpcore==1.0.5
+httpx==0.27.0
+idna==3.8
+iniconfig==2.0.0
+jmespath==1.0.1
+MarkupSafe==2.1.5
+mccabe==0.7.0
+multidict==6.0.5
+packaging==24.1
+pillow==10.4.0
+pip==22.0.2
+pluggy==1.5.0
+pycodestyle==2.11.1
+pydantic==2.8.2
+pydantic-settings==2.2.1
+pydantic_core==2.20.1
+pyflakes==3.2.0
+pytest==8.1.1
+pytest-asyncio==0.23.5.post1
+pytest-cov==4.1.0
+pytest_httpserver==1.0.10
+python-dateutil==2.9.0.post0
+python-dotenv==1.0.1
+PyYAML==6.0.1
+setuptools==59.6.0
+six==1.16.0
+sniffio==1.3.1
+starlette==0.36.3
+tomli==2.0.1
+typing_extensions==4.12.2
+urllib3==2.0.7
+uvicorn==0.28.0
+Werkzeug==3.0.4
+wrapt==1.16.0
+yarl==1.9.4

requirements.txt

@@ -1 +1,3 @@
-common-code[test] @ git+https://github.com/swiss-ai-center/common-code.git@main
+pillow~=10.4.0
+pip~=22.0.2
+setuptools~=59.6.0

src/draw_boxes/draw_boxes.py

@@ -0,0 +1,14 @@
+from PIL import Image, ImageDraw
+import io
+
+
+def draw_bounding_boxes(image, boxes):
+    imageStream = io.BytesIO(image)
+    image = Image.open(imageStream)
+    image = ImageDraw.Draw(image)
+    for elt in boxes:
+        box = elt['position']
+        x, y, w, h = box['left'], box['top'], box['width'], box['height']
+        shape = [x, y, x + w, y + h]
+        image.rectangle(shape, fill=None, outline="red")
+    return image._image

src/main.py

@@ -1,5 +1,6 @@
 import asyncio
 import time
+
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import RedirectResponse
@@ -19,15 +20,16 @@
 from contextlib import asynccontextmanager
 
 # Imports required by the service's model
-# TODO: 1. ADD REQUIRED IMPORTS (ALSO IN THE REQUIREMENTS.TXT)
+from draw_boxes.draw_boxes import draw_bounding_boxes
+import io
+import json
 
 settings = get_settings()
 
 
 class MyService(Service):
-    # TODO: 2. CHANGE THIS DESCRIPTION
     """
-    My service model
+    bounding boxes drawing service
     """
 
     # Any additional fields must be excluded for Pydantic to work
@@ -36,14 +38,12 @@ class MyService(Service):
 
     def __init__(self):
         super().__init__(
-            # TODO: 3. CHANGE THE SERVICE NAME AND SLUG
-            name="My Service",
-            slug="my-service",
+            name="Image Draw Bounding Boxes",
+            slug="image-draw-bounding-boxes",
             url=settings.service_url,
             summary=api_summary,
             description=api_description,
             status=ServiceStatus.AVAILABLE,
-            # TODO: 4. CHANGE THE INPUT AND OUTPUT FIELDS, THE TAGS AND THE HAS_AI VARIABLE
             data_in_fields=[
                 FieldDescription(
                     name="image",
@@ -52,10 +52,14 @@ def __init__(self):
                         FieldDescriptionType.IMAGE_JPEG,
                     ],
                 ),
+                FieldDescription(
+                    name="data",
+                    type=[FieldDescriptionType.APPLICATION_JSON]
+                )
             ],
             data_out_fields=[
                 FieldDescription(
-                    name="result", type=[FieldDescriptionType.APPLICATION_JSON]
+                    name="image-with-boxes", type=[FieldDescriptionType.IMAGE_PNG, FieldDescriptionType.IMAGE_JPEG]
                 ),
             ],
             tags=[
@@ -70,18 +74,26 @@ def __init__(self):
         )
         self._logger = get_logger(settings)
 
-    # TODO: 5. CHANGE THE PROCESS METHOD (CORE OF THE SERVICE)
     def process(self, data):
         # NOTE that the data is a dictionary with the keys being the field names set in the data_in_fields
         # The objects in the data variable are always bytes. It is necessary to convert them to the desired type
         # before using them.
         # raw = data["image"].data
         # input_type = data["image"].type
         # ... do something with the raw data
+        img = data['image'].data
+        img_format = data['image'].type
+        boxes_data = json.loads(data['data'].data)
+
+        img_boxes = draw_bounding_boxes(image=img, boxes=boxes_data['boxes'])
+        img_type = str(data['image'].type).split('_')[1]
+        img_byte_arr = io.BytesIO()
+        img_boxes.save(img_byte_arr, format=img_type)
+        img_byte_arr = img_byte_arr.getvalue()
 
         # NOTE that the result must be a dictionary with the keys being the field names set in the data_out_fields
         return {
-            "result": TaskData(data=..., type=FieldDescriptionType.APPLICATION_JSON)
+            "image-with-boxes": TaskData(data=img_byte_arr, type=img_format)
         }
 
 
@@ -135,19 +147,18 @@ async def announce():
         await service_service.graceful_shutdown(my_service, engine_url)
 
 
-# TODO: 6. CHANGE THE API DESCRIPTION AND SUMMARY
-api_description = """My service
-bla bla bla...
+api_description = """This microservice draws boxes on an image. It is intended to work with the
+text recognition OCR service. The bounding boxes are passed in a JSON file that corresponds to the output of
+the text recognition service.
 """
-api_summary = """My service
-bla bla bla...
+api_summary = """This microservice draws boxes on an image. It is intended to work with the
+text recognition OCR service.
 """
 
 # Define the FastAPI application with information
-# TODO: 7. CHANGE THE API TITLE, VERSION, CONTACT AND LICENSE
 app = FastAPI(
     lifespan=lifespan,
-    title="Sample Service API.",
+    title="Image Draw Bounding Boxes Service API.",
     description=api_description,
     version="0.0.1",
     contact={