Create app.py

app.py

@@ -0,0 +1,76 @@
+import streamlit as st
+import requests
+import base64
+import os
+
+# Function to encode the image to base64
+def encode_image(image_file):
+    image_bytes = image_file.read()
+    return base64.b64encode(image_bytes).decode('utf-8')
+
+def compare_images(task_description, image_1, image_2):
+    api_key = "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"
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}"
+    }
+    payload = {
+        "model": "gpt-4o-mini",
+        "messages": [
+            {"role": "system", "content": "You are an expert in analyzing progress in construction tasks based on image comparisons."},
+            {"role": "user", "content": f"Task: '{task_description}'."},
+            {"role": "user", 
+              "content": [
+                  {"type": "text", 
+                   "text": "This is the yesterday's image of task."}, 
+                  {
+                      "type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_1}"}
+                  }
+            ]},
+            {
+                "role": "user", 
+                "content": [
+                    {
+                        "type": "text", 
+                        "text": "This is today's image of task."
+                    }, 
+                    {
+                         "type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_2}"}
+                    }
+                    ]
+            },
+            {"role": "user", "content": "Now tell me is there any progress made today from yesterday in terms of task."}
+        ],
+        "max_tokens": 1000
+    }
+    response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
+    print(response.json())
+    return response.json()['choices'][0]['message']['content']
+
+# Streamlit app interface
+st.title("Construction Task Progress Analyzer")
+st.write("Upload yesterday's and today's images of the task, and describe the task to analyze progress.")
+
+task_description = st.text_input("Enter the task description:")
+col1, col2, col3, col4 = st.columns(4)
+with col1:
+    yesterday_image = st.file_uploader("Choose yesterday's image:", type=['png', 'jpg', 'jpeg'])
+with col2:
+    if yesterday_image is not None:
+        st.image(yesterday_image, caption="yesterday's image", width=100)
+with col3:
+    today_image = st.file_uploader("Choose today's image:", type=['png', 'jpg', 'jpeg'])
+with col4:
+    if today_image is not None:
+        st.image(today_image, caption="today's image", width=100)
+
+
+if st.button("Analyze Progress"):
+    if yesterday_image and today_image and task_description:
+        base64_image_1 = encode_image(yesterday_image)
+        base64_image_2 = encode_image(today_image)
+        result = compare_images(task_description, base64_image_1, base64_image_2)
+        st.write("Analysis Result:")
+        st.write(result)
+    else:
+        st.error("Please upload both images and provide the task description.")