update app.py with new image selector

app.py

@@ -6,6 +6,7 @@ import torch
 from PIL import Image
 import requests
 import os
+import random
 
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -20,6 +21,12 @@ blipprocessor = BlipProcessor.from_pretrained(model_id)
 
 im_dir = os.path.join(os.getcwd(),'images')
 
+def sample_image(im_dir=im_dir):
+  all_ims = os.listdir(im_dir)
+  new_im = random.choice(all_ims)
+  return gr.Image(label="Target Image", interactive = False, type="pil",value =os.path.join(im_dir,new_im),height=500),gr.Textbox(label="Image fname",value=new_im,interactive=False, visible=False)
+
+
 def evaluate_caption(image, caption):
     # # Pre-process image
     # image = processor(images=image, return_tensors="pt").to(device)
@@ -51,13 +58,13 @@ def evaluate_caption(image, caption):
     return blip_caption,winner
     # ,gr.Image(type="pil", value="mukherjee_kushin_WIDPICS1.jpg")
 
-
 callback = gr.HuggingFaceDatasetSaver('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', "gradioTest")
 with gr.Blocks() as demo:
   im_path_str = 'n01677366_12918.JPEG'
   im_path = gr.Textbox(label="Image fname",value=im_path_str,interactive=False, visible=False)
   # fn=evaluate_caption,
   # inputs=["image", "text"]
+ 
   
   with gr.Column():
     im = gr.Image(label="Target Image", interactive = False, type="pil",value =os.path.join(im_dir,im_path_str),height=500)
@@ -67,6 +74,7 @@ with gr.Blocks() as demo:
   with gr.Column():
     out1 = gr.Textbox(label="Player 2 (Machine) Caption",interactive=False)
     out2 = gr.Textbox(label="Winner",interactive=False)
+    reload_btn = gr.Button("Next Image")
 
 
   # live=False,
@@ -74,8 +82,9 @@ with gr.Blocks() as demo:
   callback.setup([caps, out1, out2, im_path], "flagged_data_points")
   # callback.flag([image, caption, blip_caption, winner])
   submit_btn.click(fn = evaluate_caption,inputs = [im,caps], outputs = [out1, out2],api_name="test").success(lambda *args: callback.flag(args), [caps, out1, out2, im_path], None, preprocess=False)
+  reload_btn.click(fn = sample_image, inputs=None, outputs = [im,im_path] )
   # with gr.Row():
   #     btn = gr.Button("Flag")
   # btn.click(lambda *args: callback.flag(args), [im, caps, out1, out2], None, preprocess=False)
 
-demo.launch(share=True)
+demo.launch()