Add support for S3-backed image storage

tests/fixtures/README.md

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+The two tiny ONNX models are deterministic classifiers used by the image upload API tests.
+They accept the same `[1, 224, 224, 3]` float input as the production nsfw model and return
+`[Drawings, Hentai, Neutral, Porn, Sexy]` scores. One always returns Neutral = 1 and the
+other always returns Porn = 1. They exercise the real nsfw inference path without requiring
+image fixtures.
+
+## Deterministic model fixtures
+
+To regenerate them with Python's `onnx` package:
+
+```python
+from pathlib import Path
+from onnx import TensorProto, checker, helper
+
+for name, scores in [("safe", [0., 0., 1., 0., 0.]), ("unsafe", [0., 0., 0., 1., 0.])]:
+    tensor = helper.make_tensor("probabilities", TensorProto.FLOAT, [1, 5], scores)
+    graph = helper.make_graph(
+        [helper.make_node("Identity", ["probabilities"], ["output"])],
+        "constant classifier for upload endpoint tests",
+        [helper.make_tensor_value_info("input", TensorProto.FLOAT, [1, 224, 224, 3])],
+        [helper.make_tensor_value_info("output", TensorProto.FLOAT, [1, 5])],
+        [tensor],
+    )
+    model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)], ir_version=8)
+    checker.check_model(model)
+    Path(f"tests/fixtures/image-upload-{name}.onnx").write_bytes(model.SerializeToString())
+```