Update app.py

app.py

@@ -12,34 +12,39 @@ pipes = {
     "ViT/H-14": pipeline("zero-shot-image-classification", model="OFA-Sys/chinese-clip-vit-huge-patch14"),
 }
 inputs = [
-    gr.inputs.Image(type='pil'),
-    "text",
+    gr.inputs.Image(type='pil', 
+                    label="Image 输入图片"),
+    gr.inputs.Textbox(lines=1, 
+                      label="Candidate Labels 候选分类标签"),
     gr.inputs.Radio(choices=[
                                 "ViT/B-16",
                                 "ViT/L-14", 
                                 "ViT/L-14@336px", 
                                 "ViT/H-14",
-                            ], type="value", default="ViT/B-16", label="Model"), 
+                            ], type="value", default="ViT/B-16", label="Model 模型规模"), 
+    gr.inputs.Textbox(lines=1, 
+                      label="Prompt Template Prompt模板 ({}指代候选标签)", 
+                      default="一张{}的图片。"),
 ]
 images="festival.jpg"
 
-def shot(image, labels_text, model_name):
+def shot(image, labels_text, model_name, hypothesis_template):
     labels = [label.strip(" ") for label in labels_text.strip(" ").split(",")]
     res = pipes[model_name](images=image, 
            candidate_labels=labels,
-           hypothesis_template= "一张{}的图片。")
+           hypothesis_template=hypothesis_template)
     return {dic["label"]: dic["score"] for dic in res}
 
 iface = gr.Interface(shot, 
             inputs, 
             "label", 
-            examples=[["festival.jpg", "灯笼, 鞭炮, 对联", "ViT/B-16"], 
-                      ["cat-dog-music.png", "音乐表演, 体育运动", "ViT/B-16"],
-                      ["football-match.jpg", "梅西, C罗, 马奎尔", "ViT/B-16"]],
+            examples=[["festival.jpg", "灯笼, 鞭炮, 对联", "ViT/B-16", "一张{}的图片。"], 
+                      ["cat-dog-music.png", "音乐表演, 体育运动", "ViT/B-16", "一张{}的图片。"],
+                      ["football-match.jpg", "梅西, C罗, 马奎尔", "ViT/B-16", "一张{}的图片。"]],
             description="""<p>Chinese CLIP is a contrastive-learning-based vision-language foundation model pretrained on large-scale Chinese data. For more information, please refer to the paper and official github. Also, Chinese CLIP has already been merged into Huggingface Transformers! <br><br>
             Paper: <a href='https://arxiv.org/abs/2211.01335'>https://arxiv.org/abs/2211.01335</a> <br>
             Github: <a href='https://github.com/OFA-Sys/Chinese-CLIP'>https://github.com/OFA-Sys/Chinese-CLIP</a> (Welcome to star! 🔥🔥) <br><br>
-            To play with this demo, add a picture and a list of labels in Chinese separated by commas. 上传图片，并输入多个分类标签，用英文逗号分隔。<br>
+            To play with this demo, add a picture and a list of labels in Chinese separated by commas. 上传图片，并输入多个分类标签，用英文逗号分隔。可点击页面最下方示例参考。<br>
             You can duplicate this space and run it privately: <a href='https://huggingface.co/spaces/OFA-Sys/chinese-clip-zero-shot-image-classification?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a></p>""",
             title="Zero-shot Image Classification (中文零样本图像分类)")