Release v0.2.3

README_us-EN.md

@@ -59,6 +59,7 @@ English | [简体中文](README_zh-CN.md)
   - [DWPose](https://github.com/IDEA-Research/DWPose/tree/main)
 - Union Model
   - YOLOv5-ResNet: Cascade model for detection and classification;
+  - YOLOv5-SAM
 - Lane Detection
   - [CLRNet](https://github.com/Turoad/CLRNet) 
 - OCR

README_zh-CN.md

@@ -62,6 +62,7 @@
   - [DWPose](https://github.com/IDEA-Research/DWPose/tree/main): 全身人体姿态估计模型；
 - Union Task
   - YOLOv5-ResNet：检测+分类级联模型；
+  - YOLOv5-SAM
 - Lane Detection
   - [CLRNet](https://github.com/Turoad/CLRNet) 
 - OCR
@@ -73,7 +74,7 @@
 
 ### 1.1 可执行文件
 
-- 从[百度网盘(提取码: 0awa)](https://pan.baidu.com/s/1uGRd2jRRxN9n3saM83IIEQ?pwd=0awa)下载并运行`GUI`版本直接运行。
+- 从[百度网盘(提取码: mt3q)](https://pan.baidu.com/s/1T12CaXcjMCAw5DK6w2qydA?pwd=mt3q)下载并运行`GUI`版本直接运行。
 
 注意：
 - 对于MacOS：

assets/Giraffes_at_west_midlands_safari_park.json

@@ -1,5 +1,5 @@
 {
-  "version": "0.2.2",
+  "version": "0.2.3",
   "flags": {},
   "shapes": [
     {

docs/models_list.md

@@ -57,7 +57,8 @@
 | sam_vit_l_0b3195.decoder.onnx | [SAM](https://arxiv.org/abs/2304.02643) ViT-large decoder  | [segment_anything_vit_l.yaml](../anylabeling/configs/auto_labeling/segment_anything_vit_l.yaml)  | 15.74MB  | [baidu](https://pan.baidu.com/s/1ftSh3oedErfM1TNOcjy4fQ?pwd=4oez) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/sam_vit_l_0b3195.decoder.onnx) |
 | sam_vit_l_0b3195.encoder.quant.onnx | [SAM](https://arxiv.org/abs/2304.02643) ViT-large encoder（量化版本） | [segment_anything_vit_l_quant.yaml](../anylabeling/configs/auto_labeling/segment_anything_vit_l_quant.yaml)  | 317.18MB  | [baidu](https://pan.baidu.com/s/1W8elbCXKIHk8c37_kKGl1w?pwd=a2mi) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/sam_vit_l_0b3195.encoder.quant.onnx) |
 | sam_vit_l_0b3195.decoder.quant.onnx | [SAM](https://arxiv.org/abs/2304.02643) ViT-large decoder（量化版本） | [segment_anything_vit_l_quant.yaml](../anylabeling/configs/auto_labeling/segment_anything_vit_l_quant.yaml)  | 8.34MB  | [baidu](https://pan.baidu.com/s/1LzXk0e-jvJFYYFiXYbD_vA?pwd=wgwp) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/sam_vit_l_0b3195.decoder.quant.onnx) |
-| mobile_sam.encoder.onnx | [MobileSAM](https://arxiv.org/abs/2306.14289) ViT-huge encoder  | [mobile_sam_vit_h.yaml](../anylabeling/configs/auto_labeling/mobile_sam_vit_h.yaml)  | 26.85MB  | [baidu](https://pan.baidu.com/s/1knn_NkrRAgfJms6d9FsErg?pwd=xbi6) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/mobile_sam.encoder.onnx) |
+| mobile_sam.encoder.onnx | [MobileSAM](https://arxiv.org/abs/2306.14289) encoder  | [mobile_sam_vit_h.yaml](../anylabeling/configs/auto_labeling/mobile_sam_vit_h.yaml)  | 26.85MB  | [baidu](https://pan.baidu.com/s/1knn_NkrRAgfJms6d9FsErg?pwd=xbi6) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/mobile_sam.encoder.onnx) |
+| sam_vit_h_4b8939.decoder.quant.onnx | [MobileSAM](https://arxiv.org/abs/2306.14289) decoder  | [mobile_sam_vit_h.yaml](../anylabeling/configs/auto_labeling/mobile_sam_vit_h.yaml)  | 8.34MB  | [baidu](https://pan.baidu.com/s/1L5RGeTWK7d5vkLmgir8x5w?pwd=f287) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/sam_vit_h_4b8939.decoder.quant.onnx) |
 | sam_vit_h_4b8939.encoder.quant.onnx | [SAM](https://arxiv.org/abs/2304.02643) ViT-huge encoder（量化版本） | [segment_anything_vit_h_quant.yaml](../anylabeling/configs/auto_labeling/segment_anything_vit_h_quant.yaml)  | 626.40MB  | [baidu](https://pan.baidu.com/s/1LJqKvxEmhzr8xQfwWk9SMg?pwd=n6ol) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/sam_vit_h_4b8939.encoder.quant.onnx) |
 | sam_vit_h_4b8939.decoder.quant.onnx | [SAM](https://arxiv.org/abs/2304.02643) ViT-huge decoder（量化版本） | [segment_anything_vit_h_quant.yaml](../anylabeling/configs/auto_labeling/segment_anything_vit_h_quant.yaml)  | 8.34MB  | [baidu](https://pan.baidu.com/s/1L5RGeTWK7d5vkLmgir8x5w?pwd=f287) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/sam_vit_h_4b8939.decoder.quant.onnx) |
 
@@ -102,5 +103,6 @@
 | yolox_l.onnx | [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX)（全身人体姿态估计） | [yolox_l_dwpose_ucoco.yaml](../anylabeling/configs/auto_labeling/yolox_l_dwpose_ucoco.yaml)  | 206.71MB  | [baidu](https://pan.baidu.com/s/1NpFiX1JN-0jIvd38tQIDcQ?pwd=aqk5) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/yolox_l.onnx) |
 | resnet50.onnx | [ResNet50](https://arxiv.org/abs/1512.03385)-ImageNet（检测+分类级联模型） | [yolov5s_resnet50.yaml](../anylabeling/configs/auto_labeling/yolov5s_resnet50.yaml)  | 97.42MB  | [baidu](https://pan.baidu.com/s/1byapPRVib7rarAMTmoSkKQ?pwd=xllt) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/resnet50.onnx) |
 | yolov5s.onnx | [YOLOv5](https://github.com/ultralytics/yolov5)-COCO（检测+分类级联模型） | [yolov5s_resnet50.yaml](../anylabeling/configs/auto_labeling/yolov5s_resnet50.yaml)  | 27.98MB  | [baidu](https://pan.baidu.com/s/18I8ugM29NKjNlVEsnYYuWA?pwd=z8dl) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/yolov5s.onnx) |
-
-
+| mobile_sam.encoder.onnx | [MobileSAM](https://arxiv.org/abs/2306.14289) encoder（YOLOv5-SAM） | [yolov5s_mobile_sam_vit_h.yaml](../anylabeling/configs/auto_labeling/yolov5s_mobile_sam_vit_h.yaml)  | 26.85MB  | [baidu](https://pan.baidu.com/s/1knn_NkrRAgfJms6d9FsErg?pwd=xbi6) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/mobile_sam.encoder.onnx) |
+| sam_vit_h_4b8939.decoder.quant.onnx | [MobileSAM](https://arxiv.org/abs/2306.14289) decoder（YOLOv5-SAM）  | [yolov5s_mobile_sam_vit_h.yaml](../anylabeling/configs/auto_labeling/yolov5s_mobile_sam_vit_h.yaml)  | 8.34MB  | [baidu](https://pan.baidu.com/s/1L5RGeTWK7d5vkLmgir8x5w?pwd=f287) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/sam_vit_h_4b8939.decoder.quant.onnx) |
+| yolov5s.onnx | [YOLOv5](https://github.com/ultralytics/yolov5)-COCO（YOLOv5-SAM） | [yolov5s_mobile_sam_vit_h.yaml](../anylabeling/configs/auto_labeling/yolov5s_mobile_sam_vit_h.yaml)  | 27.98MB  | [baidu](https://pan.baidu.com/s/18I8ugM29NKjNlVEsnYYuWA?pwd=z8dl) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/yolov5s.onnx) |

scripts/zip_models.py

@@ -32,6 +32,17 @@ def get_filename_from_url(url):
     if model_config["type"] in ["segment_anything", "sam_med2d"]:
         download_links.append(model_config["encoder_model_path"])
         download_links.append(model_config["decoder_model_path"])
+    elif model_config["type"] in ["yolov5_sam"]:
+        download_links.append(model_config["encoder_model_path"])
+        download_links.append(model_config["decoder_model_path"])
+        download_links.append(model_config["model_path"])
+    elif model_config["type"] in ["yolov5_cls"]:
+        download_links.append(model_config["det_model_path"])
+        download_links.append(model_config["cls_model_path"])
+    elif model_config["type"] in ["ppocr_v4"]:
+        download_links.append(model_config["det_model_path"])
+        download_links.append(model_config["rec_model_path"])
+        download_links.append(model_config["cls_model_path"])
     else:
         download_links.append(model_config["model_path"])
 
@@ -47,6 +58,33 @@ def get_filename_from_url(url):
         model_config["decoder_model_path"] = get_filename_from_url(
             model_config["decoder_model_path"]
         )
+    elif model_config["type"] in ["yolov5_sam"]:
+        model_config["encoder_model_path"] = get_filename_from_url(
+            model_config["encoder_model_path"]
+        )
+        model_config["decoder_model_path"] = get_filename_from_url(
+            model_config["decoder_model_path"]
+        )
+        model_config["model_path"] = get_filename_from_url(
+            model_config["model_path"]
+        )
+    elif model_config["type"] in ["yolov5_cls"]:
+        model_config["det_model_path"] = get_filename_from_url(
+            model_config["det_model_path"]
+        )
+        model_config["cls_model_path"] = get_filename_from_url(
+            model_config["cls_model_path"]
+        )
+    elif model_config["type"] in ["ppocr_v4"]:
+        model_config["det_model_path"] = get_filename_from_url(
+            model_config["det_model_path"]
+        )
+        model_config["rec_model_path"] = get_filename_from_url(
+            model_config["rec_model_path"]
+        )
+        model_config["cls_model_path"] = get_filename_from_url(
+            model_config["cls_model_path"]
+        )
     else:
         model_config["model_path"] = get_filename_from_url(
             model_config["model_path"]