Merge remote-tracking branch 'origin/dev' into dev

magic_pdf/model/doc_analyze_by_custom_model.py

@@ -257,13 +257,13 @@ def may_batch_image_analyze(
     if str(device).startswith('npu') or str(device).startswith('cuda'):
         gpu_memory = int(os.getenv('VIRTUAL_VRAM_SIZE', round(get_vram(device))))
         if gpu_memory is not None:
-            if gpu_memory >= 20:
+            if gpu_memory >= 16:
                 batch_ratio = 16
-            elif gpu_memory >= 15:
+            elif gpu_memory >= 12:
                 batch_ratio = 8
-            elif gpu_memory >= 10:
+            elif gpu_memory >= 8:
                 batch_ratio = 4
-            elif gpu_memory >= 7:
+            elif gpu_memory >= 6:
                 batch_ratio = 2
             else:
                 batch_ratio = 1

magic_pdf/model/sub_modules/mfr/unimernet/Unimernet.py

@@ -30,7 +30,6 @@ class UnimernetModel(object):
             self.model = self.model.to(dtype=torch.float16)
         self.model.eval()
 
-
     def predict(self, mfd_res, image):
         formula_list = []
         mf_image_list = []

projects/web_api/download_models.py

@@ -4,12 +4,12 @@ from huggingface_hub import snapshot_download
 if __name__ == "__main__":
 
     mineru_patterns = [
-        "models/Layout/LayoutLMv3/*",
+        # "models/Layout/LayoutLMv3/*",
         "models/Layout/YOLO/*",
         "models/MFD/YOLO/*",
-        "models/MFR/unimernet_small_2501/*",
-        "models/TabRec/TableMaster/*",
-        "models/TabRec/StructEqTable/*",
+        "models/MFR/unimernet_hf_small_2503/*",
+        # "models/TabRec/TableMaster/*",
+        # "models/TabRec/StructEqTable/*",
     ]
     model_dir = snapshot_download(
         "opendatalab/PDF-Extract-Kit-1.0",