From 5be2ffbd13e278f108e8f37ba439d9c51e7c5822 Mon Sep 17 00:00:00 2001
From: Glenn Jocher <glenn.jocher@ultralytics.com>
Date: Mon, 25 Mar 2024 02:00:38 +0100
Subject: [PATCH] `ultralytics 8.1.34` Inference API robust imgsz checks
(#9274)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
---
ultralytics/__init__.py | 2 +-
ultralytics/engine/results.py | 32 +++++++++++++++++++++-----------
ultralytics/utils/checks.py | 2 ++
3 files changed, 24 insertions(+), 12 deletions(-)
diff --git a/ultralytics/__init__.py b/ultralytics/__init__.py
index 9a5b1ee3..d25836a0 100644
--- a/ultralytics/__init__.py
+++ b/ultralytics/__init__.py
@@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
-__version__ = "8.1.33"
+__version__ = "8.1.34"
from ultralytics.data.explorer.explorer import Explorer
from ultralytics.models import RTDETR, SAM, YOLO, YOLOWorld
diff --git a/ultralytics/engine/results.py b/ultralytics/engine/results.py
index babe5d3b..85849c34 100644
--- a/ultralytics/engine/results.py
+++ b/ultralytics/engine/results.py
@@ -385,10 +385,10 @@ class Results(SimpleClass):
BGR=True,
)
- def summary(self, normalize=False):
+ def summary(self, normalize=False, decimals=5):
"""Convert the results to a summarized format."""
if self.probs is not None:
- LOGGER.warning("Warning: Classify task do not support `summary` and `tojson` yet.")
+ LOGGER.warning("Warning: Classify results do not support the `summary()` method yet.")
return
# Create list of detection dictionaries
@@ -396,28 +396,38 @@ class Results(SimpleClass):
data = self.boxes.data.cpu().tolist()
h, w = self.orig_shape if normalize else (1, 1)
for i, row in enumerate(data): # xyxy, track_id if tracking, conf, class_id
- box = {"x1": row[0] / w, "y1": row[1] / h, "x2": row[2] / w, "y2": row[3] / h}
- conf = row[-2]
+ box = {
+ "x1": round(row[0] / w, decimals),
+ "y1": round(row[1] / h, decimals),
+ "x2": round(row[2] / w, decimals),
+ "y2": round(row[3] / h, decimals),
+ }
+ conf = round(row[-2], decimals)
class_id = int(row[-1])
- name = self.names[class_id]
- result = {"name": name, "class": class_id, "confidence": conf, "box": box}
+ result = {"name": self.names[class_id], "class": class_id, "confidence": conf, "box": box}
if self.boxes.is_track:
result["track_id"] = int(row[-3]) # track ID
if self.masks:
- x, y = self.masks.xy[i][:, 0], self.masks.xy[i][:, 1] # numpy array
- result["segments"] = {"x": (x / w).tolist(), "y": (y / h).tolist()}
+ result["segments"] = {
+ "x": (self.masks.xy[i][:, 0] / w).round(decimals).tolist(),
+ "y": (self.masks.xy[i][:, 1] / h).round(decimals).tolist(),
+ }
if self.keypoints is not None:
x, y, visible = self.keypoints[i].data[0].cpu().unbind(dim=1) # torch Tensor
- result["keypoints"] = {"x": (x / w).tolist(), "y": (y / h).tolist(), "visible": visible.tolist()}
+ result["keypoints"] = {
+ "x": (x / w).numpy().round(decimals).tolist(), # decimals named argument required
+ "y": (y / h).numpy().round(decimals).tolist(),
+ "visible": visible.numpy().round(decimals).tolist(),
+ }
results.append(result)
return results
- def tojson(self, normalize=False):
+ def tojson(self, normalize=False, decimals=5):
"""Convert the results to JSON format."""
import json
- return json.dumps(self.summary(normalize=normalize), indent=2)
+ return json.dumps(self.summary(normalize=normalize, decimals=decimals), indent=2)
class Boxes(BaseTensor):
diff --git a/ultralytics/utils/checks.py b/ultralytics/utils/checks.py
index 5d908851..c44ac0b6 100644
--- a/ultralytics/utils/checks.py
+++ b/ultralytics/utils/checks.py
@@ -142,6 +142,8 @@ def check_imgsz(imgsz, stride=32, min_dim=1, max_dim=2, floor=0):
imgsz = [imgsz]
elif isinstance(imgsz, (list, tuple)):
imgsz = list(imgsz)
+ elif isinstance(imgsz, str): # i.e. '640' or '[640,640]'
+ imgsz = [int(imgsz)] if imgsz.isnumeric() else eval(imgsz)
else:
raise TypeError(
f"'imgsz={imgsz}' is of invalid type {type(imgsz).__name__}. "