feat(v1): add basic backend and frontend

backend/processing/services.py

@@ -0,0 +1,84 @@
+import time
+
+from django.conf import settings
+from django.utils import timezone
+
+from .algorithms import ProcessingError, decode_image, histogram, process_image
+from .models import ImageSession, ProcessingJob
+from .storage import load_image_array, payload_for_image, save_image_array
+from .tasks import run_batch_job
+
+
+def image_session_create(*, uploaded_file=None, image_base64=None):
+    if uploaded_file and uploaded_file.size > settings.MAX_UPLOAD_MB * 1024 * 1024:
+        raise ProcessingError(f"Upload exceeds {settings.MAX_UPLOAD_MB} MB.")
+
+    image = decode_image(uploaded_file=uploaded_file, base64_image=image_base64)
+    relative_path = save_image_array(image, "original")
+    hist = histogram(image)
+    session = ImageSession.objects.create(
+        original_image=relative_path,
+        width=image.shape[1],
+        height=image.shape[0],
+        channels=image.shape[2] if image.ndim == 3 else 1,
+        color_mode="RGB" if image.ndim == 3 else "L",
+        original_histogram=hist,
+        expires_at=timezone.now() + timezone.timedelta(hours=settings.IMAGE_SESSION_TTL_HOURS),
+    )
+    payload = {
+        "session_id": str(session.id),
+        "width": session.width,
+        "height": session.height,
+        "channels": session.channels,
+        "color_mode": session.color_mode,
+        "original_histogram": hist,
+        "expires_at": session.expires_at.isoformat(),
+    }
+    payload.update(payload_for_image(image, relative_path))
+    return payload
+
+
+def image_session_process(*, session, operation, params):
+    if session.expired:
+        raise ProcessingError("Image session has expired.")
+
+    started_at = time.perf_counter()
+    source = load_image_array(session.original_image)
+    result = process_image(source, operation, params)
+    relative_path = save_image_array(result, f"processed-{operation}")
+    hist = histogram(result)
+
+    session.processed_image = relative_path
+    session.processed_histogram = hist
+    session.save(update_fields=["processed_image", "processed_histogram"])
+
+    payload = {
+        "session_id": str(session.id),
+        "operation": operation,
+        "params": params,
+        "processed_histogram": hist,
+        "elapsed_ms": round((time.perf_counter() - started_at) * 1000, 2),
+    }
+    payload.update(payload_for_image(result, relative_path))
+    return payload
+
+
+def batch_job_create(*, operation, session_ids, params=None):
+    job = ProcessingJob.objects.create(operation=operation, params=params or {})
+    run_batch_job.delay(str(job.id), operation, [str(session_id) for session_id in session_ids])
+    return job
+
+
+def processing_job_payload(*, job):
+    payload = {
+        "job_id": str(job.id),
+        "operation": job.operation,
+        "status": job.status,
+        "progress": job.progress,
+        "error": job.error,
+        "result_histogram": job.result_histogram,
+    }
+    if job.result_image:
+        image = load_image_array(job.result_image)
+        payload.update(payload_for_image(image, job.result_image))
+    return payload