From 0e86b77a8442d39fcf5a8c43d9e8b81eaa0b44db Mon Sep 17 00:00:00 2001
From: Christian Schiffer <c.schiffer@fz-juelich.de>
Date: Thu, 8 Apr 2021 15:51:50 +0200
Subject: [PATCH] Implemented some functions to retrieve prediction annotations
---
atlas_controller/atlas_controller/app.py | 38 +++++++++++++++++-------
atlas_server/src/app.py | 35 ++++++++++++++++++----
2 files changed, 57 insertions(+), 16 deletions(-)
diff --git a/atlas_controller/atlas_controller/app.py b/atlas_controller/atlas_controller/app.py
index fcea2d9..1e90721 100644
--- a/atlas_controller/atlas_controller/app.py
+++ b/atlas_controller/atlas_controller/app.py
@@ -3,7 +3,7 @@ import os
import base64
from subprocess import CalledProcessError
-from flask import Flask
+from flask import Flask, request
from flask_restx import Api, Resource, fields, abort
from models import JobSchema
@@ -187,6 +187,7 @@ class Predictions(Resource):
import os
import glob
import h5py
+ import json
work_dir = "/".join([WORK_DIR_ROOT, work_dir])
if not os.path.exists(work_dir):
@@ -198,17 +199,32 @@ class Predictions(Resource):
abort(404, f"Could not find prediction directory {prediction_dir}")
return
+ # If this is True, return annotations instead of information on the files
+ annotations = request.args.get("annotations", "").lower() in ("true", )
results = []
- prediction_files = glob.glob(os.path.join(prediction_dir, "*.hdf5"))
- for prediction_file in prediction_files:
- with h5py.File(prediction_file, "r") as f:
- hw = f["pyramid/00"].shape[:2]
- results.append(
- {
- "path": prediction_file.replace(WORK_DIR_ROOT, ""),
- "shape": hw,
- }
- )
+
+ if annotations:
+ # Search for annotation files
+ prediction_files = glob.glob(os.path.join(prediction_dir, ".coordinates.json"))
+ for prediction_file in prediction_files:
+ with open(prediction_file, "r") as f:
+ prediction_files.append(
+ {
+ "path": prediction_file.replace(WORK_DIR_ROOT, ""),
+ "annotations": json.load(f)
+ })
+ else:
+ # Search for prediction files
+ prediction_files = glob.glob(os.path.join(prediction_dir, "*.hdf5"))
+ for prediction_file in prediction_files:
+ with h5py.File(prediction_file, "r") as f:
+ hw = f["pyramid/00"].shape[:2]
+ results.append(
+ {
+ "path": prediction_file.replace(WORK_DIR_ROOT, ""),
+ "shape": hw,
+ }
+ )
return results
diff --git a/atlas_server/src/app.py b/atlas_server/src/app.py
index 5d2de66..6278ac0 100644
--- a/atlas_server/src/app.py
+++ b/atlas_server/src/app.py
@@ -317,7 +317,7 @@ class TaskJob(Resource):
except JobStatusNotFoundError:
# If the job status could not be found, it could mean the job has finished to long ago
result["status"] = f"Could not determine job status for job with id {job_id}. " \
- f"This could mean that the job does not exist or finished too long ago."
+ f"This could mean that the job does not exist or finished too long ago."
return result
@@ -368,15 +368,15 @@ class TaskTileServerConfig(Resource):
with Database() as db:
project = db.get_project_by_id(project_id=project_id)
except ProjectNotFoundError:
- abort(404, f"No project found for id {project_id}")
- return
+ abort(404, f"No project found for id {project_id}")
+ return
try:
with Database() as db:
task = db.get_task_by_id(project_id=project_id, task_id=task_id)
except ProjectNotFoundError:
- abort(404, f"No task found for id {task_id}")
- return
+ abort(404, f"No task found for id {task_id}")
+ return
# Determine
work_dir = f"atlas_ui_project{project_id}_task{task_id}"
@@ -517,6 +517,31 @@ class AnnotationImportExport(Resource):
"status": "ok",
}
+
+@annotation_namespace.route("/<int:project_id>/tasks/<int:task_id>")
+class PredictionAnnotationExport(Resource):
+ @annotation_namespace.doc("Retrieve annotations based on predictions of a specific task")
+ def get(self, project_id, task_id):
+ import requests
+ from .config import ATLAS_CONTROLLER_URL
+
+ # Determine
+ work_dir = f"atlas_ui_project{project_id}_task{task_id}"
+ # Query predictions
+ result = requests.get(url=f"{ATLAS_CONTROLLER_URL}/predictions/{work_dir}?annotations=true")
+ if result.status_code >= 400:
+ abort(404, f"Failed to find predictions")
+ return
+ result = result.json()
+
+ return {
+ "project_id": project_id,
+ "task_id": task_id,
+ "path": result["path"],
+ "annotations": result["annotations"],
+ }
+
+
# -----------------------------------
# Main entry point
# -----------------------------------
--
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