HF clip_score计算 fromdiffusersimportStableDiffusionPipeline,EulerDiscreteSchedulerimporttorchimportpandasaspdfromPILimportImageimportnumpyasnp# for clip_scorefromtorchmetrics.functional.multimodalimportclip_scorefromfunctoolsimportpartial# 加载CLIP模型clip_score_fn=partial(clip_score,model_name_or_path="openai/c...
After using the stronger ResNet-101 backbone network, we achieved even higher scores, with a score of 67.8% in fold0 and an average score of 65.9% across all four folds in the one-shot setting. In the five-shot setting, we improved the score of fold0 to 72.8% and the average score...
right"},{"text": "the blue car is on the right, the red car is on the left"},{"text": "the blue car is on top of the red car"},{"text": "the blue car is below the red car"}]}],"execEndpoint":"/rank"}'\|jq".data[].matches[] | (.text, .scores.clip_score.value...
for match, score in matches: res += ", " + match except Exception: print(f"Error interrogating", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) self.unload() return res1 change: 1 addition & 0 deletions 1 modules/paths.py Original file line numberDiff line number...
["a photo of a cat", "a photo of a dog"], images=image, return_tensors="pt", padding=True) outputs = model(**inputs) logits_per_image = outputs.logits_per_image # this is the image-text similarity score probs = logits_per_image.softmax(dim=1) # we can take the softmax ...
(15). (15)Accuracy (Acc)=TP+TNTP+TN+FN+FPPrecision ( Pre )=TPTP+FPRecall (Rec )=TPTP+FNF1-Score=2Pre⋅RecPre+Rec TP (true positive) denotes the number of fake news items actually correctly identified by the model, and TN (true negative) denotes the number of true news items ...
tensor([0.0047, 0.0013, 0.0029, 0.9844, 0.0067], grad_fn=<SelectBackward0>) 3、创建训练数据集 现在我们知道如何应用 CLIP 来预测字幕,我们可以构建一个训练数据集来微调模型。让我们获取随机 10 幅图像的相似度分数(您可以将其增加到更大的尺寸,但在这里我们将保持较小尺寸,以便于在笔记本电脑 CPU 上快速...
CLIP在结构化的文本-图像匹配上表现不够,如通过clip score并不能区别一张图是人咬狗和狗咬人. 作者认为造成这个问题的原因是CLIP在学习多模态场景中的representations时未能充分利用结构化知识. 文章提出 Structure-CLIP ,一个端到端的框架,通过集成场景图知识来增强多模态结构化表示. ...
To obtain a cutoff for further analysis, RBPs were sorted by the maximum position-wise relative information on the 45S rRNA precursor, and at each value, the F1 score was calculated (defined as (2 × TP)/(2 × TP + FP + FN)) using the definitions described above....
:return: IoU score """ # 计算intersection面积 ixmin = max(pred_bbox[0], gt_box[0]) iymin = max(pred_bbox[1], gt_box[1]) ixmax = min(pred_bbox[2], gt_box[2]) iymax = min(pred_bbox[3], gt_box[3]) interWidth = iymax - iymin ...