Load pandas df, load dataset, print first 12 images. get image database (merve/coco). Randomly select image (include dir, root, file)

app.py

@@ -3,5 +3,57 @@ import gradio as gr
 def greet(name):
     return "Hello " + name + "!!"
 
+
+
+# Load vision capability to support image display
+pip install datasets[vision]
+
+# Load pandas for grid display
+pip install pandas
+import pandas as pd
+
+
+# Load database (merve/coco)
+from datasets import load_dataset
+dataset = load_dataset("merve/coco")
+
+df = pd.dataset
+print(df.head(12))
+
+
+# Get image database
+##curl -X GET \
+##     "https://datasets-server.huggingface.co/first-rows?dataset=merve%2Fcoco&config=default&split=validation"
+
+# Load transformer Salesforce/blip image captioning
+# Load model directly
+##from transformers import AutoProcessor, AutoModelForVision2Seq
+
+##processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
+##model = AutoModelForVision2Seq.from_pretrained("Salesforce/blip-image-captioning-large")
+
+
+import os
+import random
+
+path = "https://huggingface.co/Salesforce/blip-image-captioning-large"
+
+images = []
+
+# This will get each root, dir and file list in the path specified recursively (like the "find" command in linux, but separating files, from directories, from paths).
+# root is the full path from your specified path to the the directory it is inspecting
+# dirs is a list containing all the directories found in the current inspecting directory
+# files is a list containing all the files found in the current inspecting directory
+for root, dirs, files in os.walk(path):
+    # This will filter all the .png files in case there is something else in the directory
+    # If your directory only has images, you can do this:
+    # images = files
+    # instead of filtering the '.png' images with the for loop // filter for jgp
+    for f in files:
+        if f[-4:] == '.jpg':
+            images.append(f)
+
 demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+
+print(random.choice(images))
 demo.launch()