算法更改

GFS-client/detect_results.json

@@ -0,0 +1,28 @@
+{
+    "shapes": [
+        {
+            "bbox": [
+                742,
+                409,
+                2126,
+                409,
+                2126,
+                1052,
+                742,
+                1052
+            ],
+            "category": "Kitchen_Cabinet",
+            "color": [
+                190,
+                255,
+                220
+            ],
+            "label": "25",
+            "name": "橱柜"
+        }
+    ],
+    "imageHeight": 2048,
+    "imagePath": "KJ-vYL6GFH2fYw_30.jpg",
+    "imageWidth": 4096,
+    "version": "4Dage_Furniture_Detection_0.0.1"
+}

GFS-client/python-versions.txt

@@ -0,0 +1 @@
+3.10

GFS-client/requirements.txt

@@ -0,0 +1,14 @@
+open3d==0.19.0
+numpy==2.2.0
+typing==3.7.4.3
+opencv-python==4.12.0.88
+requests==2.28.1
+
+##import sys
+##import time
+##from itertools import groupby
+##import os
+##import shutil
+##import zipfile
+##import json
+##import argparse

depoly_modify/run_all.sh

@@ -18,7 +18,7 @@ echo "========================================================"
 
 
 echo ""
-echo "--- [步骤 1/3] 正在执行 denosie_downsampling_ply.py (点云前处理阶段) ---"
+echo "--- [步骤 1/3] 正在执行 denosie_downsampling_ply.py (点云预处理阶段) ---"
 python denosie_downsampling_ply.py -i "${INPUT_FOLDER}"
 echo "✅ 点云采样和去噪执行完成。"
 

depoly_modify/save_result.py

@@ -8,6 +8,29 @@ from itertools import groupby
 import argparse
 
 
+CLASS_MAPPING = {
+    'refrigerator': {'id': '0', 'name': '冰箱'},
+    'desk': {'id': '1', 'name': '书桌'},
+    'curtain': {'id': '2', 'name': '窗帘'},
+    'sofa': {'id': '3', 'name': '沙发'},
+    'bookshelf': {'id': '4', 'name': '书架'},
+    'bed': {'id': '5', 'name': '床'},
+    'table': {'id': '6', 'name': '桌子'},
+    'window': {'id': '7', 'name': '窗户'},
+    'cabinet': {'id': '8', 'name': '橱柜'},
+    'door': {'id': '9', 'name': '门'},
+    'chair': {'id': '10', 'name': '椅子'},
+    'floor': {'id': '11', 'name': '地板'},
+    'wall': {'id': '12', 'name': '墙'},
+    'sink': {'id': '13', 'name': '水槽'},
+    'toilet': {'id': '14', 'name': '马桶'},
+    'bathtub': {'id': '15', 'name': '浴缸'},
+    'shower curtain': {'id': '16', 'name': '浴帘'},
+    'picture': {'id': '17', 'name': '画'},
+    'counter': {'id': '18', 'name': '柜台'},
+}
+
+
 # ==============================================================================
 # 优化算法辅助函数
 # ==============================================================================
@@ -255,26 +278,45 @@ def process_and_draw_bboxes(picture_name, floor_path, instances_path, floor_id,
         filtered_bbox_data = post_process_in_2d(instances_with_pixel_boxes, x_m_per_px, y_m_per_px)
         print("2D后处理完成。")
         
-        instances_2d_data = []
+        img_height, img_width, _ = img.shape
+        shapes = []
         for item in filtered_bbox_data:
             min_x, min_y, max_x, max_y = item['bbox_2d_pixels']
-            label = item["label"]
-            color_bgr = (item["color"][2], item["color"][1], item["color"][0])
-
-            instances_2d_data.append({"label": label, "color": item["color"], "bbox_2d": item['bbox_2d_pixels']})
+            category = item["label"]
+            color_rgb = item["color"]
+            color_bgr = (color_rgb[2], color_rgb[1], color_rgb[0])
 
             cv2.rectangle(img, (min_x, min_y), (max_x, max_y), color_bgr, 2)
             font = cv2.FONT_HERSHEY_SIMPLEX
-            (text_w, text_h), _ = cv2.getTextSize(label, font, 0.5, 1)
+            (text_w, text_h), _ = cv2.getTextSize(category, font, 0.5, 1)
             label_y = min_y - 10 if min_y - 10 > text_h else min_y + text_h + 10
             cv2.rectangle(img, (min_x, label_y - text_h - 5), (min_x + text_w, label_y + 5), color_bgr, -1)
-            cv2.putText(img, label, (min_x, label_y), font, 0.5, (255, 255, 255), 1, cv2.LINE_AA)
+            cv2.putText(img, category, (min_x, label_y), font, 0.5, (255, 255, 255), 1, cv2.LINE_AA)
+
+            bbox_poly = [min_x, min_y, max_x, min_y, max_x, max_y, min_x, max_y]
+            class_info = CLASS_MAPPING.get(category, {'id': '-1', 'name': '未知'})
+
+            shapes.append({
+                "bbox": bbox_poly,
+                "category": category,
+                "color": color_rgb,
+                "label": class_info['id'],
+                "name": class_info['name']
+            })
+
+        output_json_data = {
+            "shapes": shapes,
+            "imageHeight": img_height,
+            "imagePath": os.path.basename(picture_name),
+            "imageWidth": img_width,
+            "version": "4Dage_Furniture_Detection_0.0.1"
+        }
 
         os.makedirs(os.path.dirname(output_image_path), exist_ok=True)
         os.makedirs(os.path.dirname(output_json_path), exist_ok=True)
         cv2.imwrite(output_image_path, img)
         with open(output_json_path, 'w', encoding='utf-8') as f:
-            json.dump(instances_2d_data, f, indent=4)
+            json.dump(output_json_data, f, ensure_ascii=False, indent=4)
         print(f"\n处理完成！2D结果已保存到: {output_image_path} 和 {output_json_path}")
         return output_json_path, output_image_path