### What problem does this PR solve? ### Type of change - [x] Performance Improvementtags/v0.16.0
| @@ -78,7 +78,7 @@ class LayoutRecognizer(Recognizer): | |||
| "x0": b["bbox"][0] / scale_factor, "x1": b["bbox"][2] / scale_factor, | |||
| "top": b["bbox"][1] / scale_factor, "bottom": b["bbox"][-1] / scale_factor, | |||
| "page_number": pn, | |||
| } for b in lts if float(b["score"]) >= 0.8 or b["type"] not in self.garbage_layouts] | |||
| } for b in lts if float(b["score"]) >= 0.4 or b["type"] not in self.garbage_layouts] | |||
| lts = self.sort_Y_firstly(lts, np.mean( | |||
| [lt["bottom"] - lt["top"] for lt in lts]) / 2) | |||
| lts = self.layouts_cleanup(bxs, lts) | |||
| @@ -354,16 +354,9 @@ def embedding(docs, mdl, parser_config=None, callback=None): | |||
| tk_count = 0 | |||
| if len(tts) == len(cnts): | |||
| tts_ = np.array([]) | |||
| for i in range(0, len(tts), batch_size): | |||
| vts, c = mdl.encode(tts[i: i + batch_size]) | |||
| if len(tts_) == 0: | |||
| tts_ = vts | |||
| else: | |||
| tts_ = np.concatenate((tts_, vts), axis=0) | |||
| tk_count += c | |||
| callback(prog=0.6 + 0.1 * (i + 1) / len(tts), msg="") | |||
| tts = tts_ | |||
| vts, c = mdl.encode(tts[0: 1]) | |||
| tts = np.concatenate([vts for _ in range(len(tts))], axis=0) | |||
| tk_count += c | |||
| cnts_ = np.array([]) | |||
| for i in range(0, len(cnts), batch_size): | |||