csv

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")
 
@@ -73,10 +73,10 @@ def url_infer_and_calculate(url, location, unit="pixels", conversion_factor=1, c
         # Create a pandas DataFrame for reporting
         df = pd.DataFrame([{'Number': index+1, 'URL': url, 'Location': location, 'corrosion_areas': corrosion_areas, 'Recommendation': corrosion_areas['recommendation']} for index in range(len(corrosion_areas))])
 
-        # Write DataFrame to a string in CSV format
-    csv_string = df.to_csv(index=False)
+        # 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, csv_string
+        return img, corrosion_areas, prediction_json
 
     except Exception as e:
         return {"error": str(e)}
@@ -87,7 +87,7 @@ 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"),
@@ -95,7 +95,7 @@ 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", gr.outputs.Textbox(label="CSV Data")],
+    outputs=[gr.outputs.Image(type="pil"), "json", "json"],
     title="Tim CCG",
     description="Enter the URL of an image to perform rust detection and calculate corrosion areas.",
 )