csv 1

app.py

@@ -7,7 +7,7 @@ import requests
 from io import BytesIO
 import pandas as pd
 import os
-import io
+
 # Initialize Roboflow with your API key
 rf = Roboflow(api_key="kKDoCn3ABT9AKeFQDCB4")
 
@@ -52,7 +52,6 @@ def get_inspection_recommendation(total_area):
         return "Immediate inspection required."
 
 # Define a Gradio interface to input a URL, run inference, and calculate corrosion areas
-#def url_infer_and_calculate(url, location, unit="pixels", conversion_factor=1):
 def url_infer_and_calculate(url, location, unit="pixels", conversion_factor=1, corrosion_type="", inspection_standards=[], ndt_methods=[], manual_recommendation="", supporting_data=""):
     try:
         # Run inference using the Roboflow script
@@ -76,7 +75,10 @@ def url_infer_and_calculate(url, location, unit="pixels", conversion_factor=1, c
         # Write DataFrame to local CSV file with index included immediately after creating it.
         df.to_csv('Corrosion_Report.csv', index=False)
 
-        return img, corrosion_areas, prediction_json
+        # Write DataFrame to a string in CSV format
+        csv_string = df.to_csv(index=False)
+
+        return img, corrosion_areas, prediction_json, csv_string
 
     except Exception as e:
         return {"error": str(e)}
@@ -87,7 +89,7 @@ iface = gr.Interface(
     inputs=[
       gr.inputs.Textbox(label="Enter the URL of an image"),
       gr.inputs.Textbox(label="Enter the Location"),
-      gr.inputs.Dropdown(choices=["pixels", "cm"], label="Area Unit"),
+      gr.inputs.Dropdown(choices=["pixels", "cm??"], label="Area Unit"),
       gr.inputs.Textbox(label="Conversion Factor"),
       gr.inputs.Textbox(label="Enter the Corrosion Type"),
       gr.inputs.CheckboxGroup(choices=[f"Standard {i+1}" for i in range(10)], label="Inspection Standards"),
@@ -95,22 +97,10 @@ iface = gr.Interface(
       gr.inputs.Textbox(label="Enter Manual Recommendation"),
       gr.inputs.Textbox(lines=5, label="Enter Supporting Data URLs (separated by commas)")
     ],
-    outputs=[gr.outputs.Image(type="pil"), "json", "json"],
+    outputs=[gr.outputs.Image(type="pil"), "json", "json", gr.outputs.Textbox(label="CSV Data")],
     title="Tim CCG",
     description="Enter the URL of an image to perform rust detection and calculate corrosion areas.",
 )
 
 # Launch the Gradio interface
 iface.launch(debug=False, share=False)
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